MIN Faculty
Department of Informatics
Knowledge Technology

Prof. Dr. Stefan Wermter

Full Professor in Computer Science
Head of Knowledge Technology

Contact Info

Address: University of Hamburg
Department of Computer Science
Knowledge Technology, WTM, Haus F
Vogt Koelln Str. 30
22527 Hamburg
Germany
Office: F-230
Phone: +49 40 428 83 2434
Fax: +49 40 428 83 2515
Secretary: +49 40 428 83 2433
Email: wermter at informatik dot uni-hamburg dot de


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Research Interests


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Short Curriculum Vitae


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Research Projects

Recently I have coordinated or participated in a number of projects, including:
A list of current and recent project can be found at the Project page of the Knowledge Technology research group.


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PhD Student Supervision

Completed and awarded (only recent ones since 2002):

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Recent Activities in Editorial Boards and Programme Committees


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Job Openings and Research Topics


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Teaching

I have taught mainly in the areas of:


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Organised Events


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Book reviews for Cognitive Systems Research welcome


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Books, Special Issues and Theses

S. Wermter, M. Page, M. Knowles, V. Gallese, F. Pulvermuller and J. Taylor. Neural Network: Special Issue on What it Means to Communicate. Volume 22, Number 2, March, 2009.

 

Wermter S., Palm G., Elshaw M. (Eds.) Biomimetic Neural Learning for Intelligent Robots. Springer, Heidelberg, Germany. 2005.


S. Wermter S., Austin J., Willshaw D. (Eds.) Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany, 2001

S. Wermter, R. Sun (Eds.) Hybrid Neural Systems. Springer Verlag, Heidelberg, 2000.

S. Wermter, E. Riloff, G. Scheler (Ed). Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing Springer Verlag, Berlin, 1996.

 

Wermter S. 1995. Hybrid Connectionist Natural Language Processing. Chapman and Hall, International Thomson Computer Press, London, UK, 1995.

 

Wermter S. Learning of Robust Language Processing in Hybrid Connectionist Architectures. Higher Doctorate (Habilitation) thesis. Department of Computer Science, University of Hamburg, Hamburg, Germany. 1998. (in German) 302pp.

 

 
Wermter S. A Hybrid Connectionist Approach for a Scanning Understanding of Natural Language Phrases. Doctoral thesis, Department of Computer Science, University of Hamburg, Hamburg, Germany. 1993.  


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Journals and Book Chapters

Yan, W., Weber, C., Wermter, S. Learning indoor robot navigation using visual and sensorimotor map information. Frontiers in Neurorobotics, Vol. 7(15), 13 p., 10.3389/fnbot.2013.00015, 2013.

 

Tripathi, N., Oakes, M., Wermter, S. Hybrid classifiers based on semantic data subspaces for two-level text categorization. International Journal of Hybrid Intelligent Systems, Vol. 10(1), pp. 33-41, IOS Press Amsterdam, doi:10.3233/HIS-130163, 2013.

 

Yan, W., Torta, E., van der Pol, D., Meins, N., Weber, C., Cuipers, R.H., Wermter, S. Learning Robot Vision for Assisted Living. In Garcia-Rodriguez, J., Cazorla, M., editors, Robotic Vision: Technologies for Machine Leaning and Vision Applications, ch. 15, pp. 257-280, IGI Global, 2013.

 

Zhong, J., Weber, C., Wermter, S. A Predictive Network Architecture for a Robust and Smooth Robot Docking Behavior. Paladyn. Journal of Behavioral Robotics, Vol. 3(4), pp. 172-180, Springer, 2012.

 

Navarro, N., Weber, C., Schroeter, P., Wermter, S. Real-world reinforcement learning for autonomous humanoid robot docking. Robotics and Autonomous Systems, Vol. 60(11), pp. 1400-1407, 2012.

 

Yan, W., Weber, C., Wermter, S. A hybrid probabilistic neural model for person tracking based on a ceiling-mounted camera. Ambient Intelligence and Smart Environments, Vol. 3(3), pp. 237-252, IOS Press Amsterdam, 2011.

 

Tripathi, N., Oakes, M., Wermter, S. Semantic subspace learning for text classification using hybrid intelligent techniques. International Journal of Hybrid Intelligent Systems, Vol. 8(2), pp. 99-114, IOS Press Amsterdam, 2011.

 

Liu J., Perez-Gonzalez D., Rees A., Erwin H., Wermter S. A biologically inspired spiking neural network model of the auditory midbrain for sound source localisation. Neurocomputing. Vol. 74, pp. 129-139, 2010. (Elsevier)

 

Ravulakollu, K., Knowles, M., Liu, J., Wermter, S. Towards Computational Modelling of Neural Multimodal Integration Based on the Superior Colliculus Concept. Innovations in Neural Information Paradigms and Applications, Volume 247, Springer Berlin / Heidelberg, pp. 269-291, 2009

 

Muse, D., Wermter, S. Actor-Critic Learning for Platform-Independent Robot Navigation. Cognitive Computation, Volume 1(3), Springer New York, pp. 203-220, 2009

 

Wermter, S., Page, M., Knowles, M., Gallese, V., Pulvermüller, F., Taylor, J. Multimodal communication in animals, humans and robots: An introduction to perspectives in brain-inspired informatics. Neural Networks, Volume 22(2), pp. 111-115. www.elsevier.com/locate/neunet. 2009.

 

Murray, J., Erwin H., and Wermter S. Robotic sound-source localisation architecture using cross-correlation and recurrent neural networks. Neural Networks Volume , 22(2), pp. 173-189. www.elsevier.com/locate/neunet. 2009.

 

 
Wermter, S. and HIS group. Hybrid Intelligent Systems. NETWorks - The Science Engineering and Technology magazine for North East England. Medical Devices and Instrumentation. Issue 5, pp.14-15, Spring, 2008.

 

Hung, C. and Wermter, S. A novel self-organising clustering model for time-event documents. The Electronic Library, vol. 26, no. 2, pp. 260-272. 2008, SSCI.

 

N. Bellotto, K. Burn, E. Fletcher, and S. Wermter. Appearance-based localization for mobile robots using digital zoom and visual compass, Robotics and Autonomous Systems, Vol. 56, Issue 2, pp. 143-156, February 2008.

 

C. Weber, M. Elshaw, S. Wermter, J. Triesch and C. Willmot. Reinforcement Learning Embedded in Brains and Robots, In: Weber, C., Elshaw M., and Mayer N. M. (Eds.) Reinforcement Learning: Theory and Applications. pp. 119-142, 2008, I-Tech Education and Publishing, Vienna, Austria.

 

Weber, C., Elshaw, M., Triesch, J. and Wermter, S. Neural Control of Actions Involving Different Coordinate Systems. In Hackel, M., Humanoid Robots: Human-like Machines, pp. 577-600, Itech, Vienna, Austria, June 2007.

 

Weber C., Wermter S. A Self-Organizing Map of Sigma-Pi Units. Neurocomputing. Vol. 70, pp. 2552-2560, 2007 (Elsevier)

 

Garfield S., Wermter S., Call Classification using Recurrent Neural Networks, Support Vector Machines and Finite State Automata. Knowledge and Information Systems: An International Journal, Vol 9,2, pp. 131-156 2006.

 

Panchev C., Wermter S., Temporal Sequence Detection with Spiking Neurons: Towards Recognizing Robot Language Instruction. Connection Science, Vol 18,1, pp. 1-22, 2006.

 

Muse D., Weber C., and Wermter, S. Robot Docking Based on Omnidirectional Vision and Reinforcement Learning. Knowledge-Based Systems, Vol 19, 5, pp. 324-332 2006. (Elsevier)

 

Weber C., Muse D., Elshaw M., and Wermter, S. A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot. Knowledge-Based Systems, 19(5), 348-355, 2006. (Elsevier)

 

Weber C., Wermter S., and Elshaw M. A hybrid generative and predictive model of the motor cortex. Neural Networks, Vol. 19(4), pp. 339-353. 2006.

 

Malone J., McGarry K., Wermter S., and Bowerman C. Data mining using rule extraction from Kohonen self-organising maps, Neural Computing Applications, Vol. 15 (1), pp. 9-17, 2006.

 

Garfield S., Wermter S., and Devlin S. Spoken Language Classification using Hybrid Classifier Combination. International Journal of Hybrid Intelligent Systems Vol. 2, No.1, pp.13-33, 2005.

 

Chokshi K., Wermter S., Panchev C., Burn K. Image Invariant Robot Navigation Based on Self Organising Neural Place Codes. In Wermter S., Palm G., Elshaw M., Biomimetic Neural Learning for Intelligent Robots, pp.74-88, 2005.

 

Murray J., Erwin H., Wermter S. A Hybrid Architecture using Cross-Correlation and Recurrent Neural Networks for Acoustic Tracking in Robots. In Wermter S., Palm G., Elshaw M., Biomimetic Neural Learning for Intelligent Robots, pp. 55-73, 2005.

 

Wermter S., Weber C., Elshaw M., Gallese, V. Pulvermüller F. Grounding Neural Robot Language in Action. In Wermter S., Palm G., Elshaw M. Biomimetic Neural Learning for Intelligent Robots, pp. 162-181, 2005.

 

Wermter S., Palm G., Weber C., Elshaw M. Towards Biomimetic Neural Learning for Intelligent Robots. In Wermter S., Palm G., Elshaw M., Biomimetic Neural Learning for Intelligent Robots, pp. 1-18, 2005.

 

Wermter S., Weber C., Elshaw M., Associative Neural Models for Biomimetic Multi-modal Learning in a Mirror Neuron-based Robot. In Cangelosi A., Bugmann G. Borisyuk R. (Eds.), Modeling Language, Cognition and Action. Singapore: World Scientific. pp. 31-46, 2005.

 

Hung C., Wermter S. Neural Network-based Document Clustering using WordNet Ontologies. International Journal of Hybrid Intelligent Systems, Vol. 1, pp. 127-142, 2004.

 

Cox, S., Oakes, M., Wermter, S.and Hawthorne, M, AudioMine: Medical Data Mining in Heterogeneous Audiology Records. International Journal of Computational Intelligence, Vol. 1, pp. 1-12, 2004.

 

Weber C., Wermter S., Zochios A. Robot Docking with Neural Vision and Reinforcement. Knowledge Based Systems, Vol. 12, No. 2-4, pp. 165-72, 2004.

 

Panchev C., Wermter S.,  Spike-timing-dependent Synaptic Plasticity: From Single Spikes to Spike Trains. Neurocomputing, Vol. 58-60, pp. 365-371, 2004.

 

Wermter S., Weber C., Elshaw M., Panchev C., Erwin H., Pulvermüller F., Towards Multimodal Neural Robot Learning. Robotics and Autonomous Systems Journal, Vol. 47, No. 2-3, pp. 171-175, 2004.

 

Hung C., Wermter S., Smith P. Hybrid Neural Document Clustering Using Guided Self-organisation and WordNet.IEEE Intelligent Systems. pp. 68-77, March/April 2004. 2004 IEEE.

 

Garfield, S, Wermter S., Recurrent Neural Learning for Classifying Spoken Utterances. Expert Update, Special Issue on Neural Language Processing, Vol. 6, No. 3, pp. 31-36. 2003.

 

Arevian G., Wermter S., Panchev C. Symbolic State Transducers and Recurrent Neural Preference Machines for Text Mining. International Journal on Approximate Reasoning, Vol. 32, No. 2/3, pp. 237-258, 2003. Elsevier.

 

Wermter S., Elshaw M., Farrand S.  A Modular Approach to Self-organisation of Robot Control Based on Language Instruction. Connection Science, Vol. 15, No 2-3, pp. 73-94, 2003.

 

Wermter S., Elshaw M. Learning Robot Actions Based on Self-organising Language Memory. Neural Networks, Vol. 16, No. 5-6, pp. 691-699, 2003.

 

Wermter S., Panchev C. Hybrid Preference Machines based on Inspiration from Neuroscience. Cognitive Systems Research. Vol. 3, No. 2, pp. 255-270, 2002. Elsevier.

 

Womble, S., Wermter S. Mirror Neurons and Feedback Learning. In Stamenov, M. I. and Gallese, V. Mirror Neurons and the Evolution of Brain and Language. John Benjamins Publishing Company, Amsterdam, pp. 353-362, 2002.

 

 
McGarry K., Wermter S., MacIntyre J. The Extraction and Comparison of Knowledge From Local Function Networks International Journal of Computational Intelligence and Applications, Vol. 1 Issue 4, pp: 369-382, 2001.

 

 
Wermter S., Austin J., Willshaw D., Elshaw M. Towards Novel Neuroscience-inspired Computing. In Wermter S., Austin J. and Willshaw D. Emergent Neural Computational Architectures based on Neuroscience. Springer, Heidelberg, Germany. pp. 1-19, 2001.

 

Wermter S., Sun R. The Present and the Future of Hybrid Symbolic Systems. AI Magazine. Spring, pp. 123-126. 2001.

 

 
Wermter S. The Hybrid Approach to Artificial Neural Network-based Language Processing. In: Dale R., Moisl H. and Somers H. (Ed.) Handbook of Natural Language Processing. p. 823-846. Marcel Dekker. 2000.

 

 
Wermter S. Neural Network Agents for Learning Semantic Text Classification. Information Retrieval. Vol. 3, No. 2, p. 87-103. 2000.

 

Wermter S. Neural Fuzzy Preference Integration using Neural Preference Moore Machines. International Journal of Neural Systems. Vol. 10, No. 4, pp. 287-309, 2000.

 

Wermter S. Knowledge Extraction from Transducer Neural Networks. Journal of Applied Intelligence. Vol. 12, p. 27-42. 2000.

 

Wermter S., Arevian G., Panchev C. Towards Hybrid Neural Learning Internet Agents. In: Wermter S., Sun R. (Ed.) Hybrid Neural Systems. p. 160-176. Springer, Heidelberg, Germany. 2000.

 

McGarry K., Wermter S., MacIntyre J. Hybrid Neural Systems: From Simple Coupling to Fully Integrated Neural Networks. Neural Computing Surveys. Vol. 2. p. 62-94. 1999.

 

Wermter S., Weber, V. SCREEN: Learning a Flat Syntactic and Semantic Spoken Language Analysis Using Artificial Neural Networks. Journal of Artificial Intelligence Research. Vol. 6, No. 1, p. 35-85. 1997.

 

Wermter S., Hannuschka R. A Connectionist Model for the Interpretation of Metaphors. In: Dorffner G. (Ed.) Neural Networks and a New AI. p. 255-276, Thomson International, London, UK. 1997.

 

 
Wermter S., Weber, V. Interactive Spoken-Language Processing in a Hybrid Connectionist System SCREEN. IEEE Computer Journal. p. 65-74, July 1996.

 

 
Weber V., Wermter S. Using Hybrid Connectionist Learning for Speech/Language Analysis. In S. Wermter, E. Riloff, G. Scheler (Ed.) Connectionist, Statistical and Symbolic Approaches to Learning for Natural Language Processing. p. 87-101, Springer Verlag, Berlin. 1996.

 

Weber V., Wermter S. Towards Learning Semantics of Spontaneous Dialog Utterances in a Hybrid Framework. In: J. Hallam (Ed.) Hybrid Problems, Hybrid Solutions, p. 229-238, IOS Press, Amsterdam. 1995.

 

Wermter S., Lehnert W. G. A Parallel Model for Compositional Similarity of Natural Language Concepts. In: Hahn U., Adriaens G. (Eds.) Parallel Natural Language Processing. Ablex Publishers, Norwood, NJ. 1994.

 

 
Wermter S. 1993. Konnektionistische/Hybride Verarbeitung Natürlicher Sprache. Künstliche Intelligenz. Vol. 93, No. 1, p. 42-44.

 

 
Wermter S., Lehnert W. G. 1992. Noun Phrase Analysis with Connectionist Networks. In: Reilly R., Sharkey N. (Eds.) Connectionist Approaches to Language Processing, p. 75-95, Lawrence Erlbaum Associates, Hillsdale, NJ.

 

 
Wermter S., Lehnert W. G. 1990. A Survey of Question Answering in Natural Language Processing. In: Zwaan R. A., Meutsch D. (Eds.) Computer Models and Technology in Media Research. North Holland, Amsterdam.

 

 
Wermter S., Lehnert W. G. A Hybrid Symbolic/Connectionist Model for Noun Phrase Understanding. Connection Science. Vol. 1 No. 3, p. 255-272. 1989.

 

 


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Refereed Proceedings Publications

Heinrich, S., Weber, C., Wermter, S. Embodied Language Understanding with a Multiple Timescale Recurrent Neural Network. Proceedings of the 23rd International Conference on Artificial Neural Networks (ICANN 2013), LNCS 8131, pp. 216-223, Springer Heidelberg. Sofia, BG, September 2013.

 

Dávila-Chacón, J., Magg, S., Liu, J., Wermter, S. Neural and Statistical Processing of Spatial Cues for Sound Source Localisation, Proceedings of International Joint Conference on Neural Networks (IJCNN 2013), pp. 1274-1281, IEEE. Dallas, US, August 2013.

 

Parisi, G., Wermter, S. Hierarchical SOM-Based Detection of Novel Behavior for 3D Human Tracking. Proceedings of International Joint Conference on Neural Networks (IJCNN 2013), pp. 1380-1387, IEEE. Dallas, US, August 2013.

 

Meins, N., Magg, S., Wermter, S. Neural Hopfield-ensemble for multi-class head pose detection. Proceedings of International Joint Conference on Neural Networks (IJCNN 2013), pp. 1327-1334, IEEE. Dallas, US, August 2013.

 

Bauer, J., Wermter, S. Self-Organized Neural Learning of Statistical Inference from High-Dimensional Data. International Joint Conference on Artificial Intelligence (IJCAI-13), pp. 1226-1232, AAAI Press. Beijing, CN, August 2013.

 

Bauer, J., Wermter, S. Learning Multi-Sensory integration with Self-Organization and Statistics. Garcez, A., Lamb, L., Hitzler, P. (Editors), Ninth International Workshop on Neural-Symbolic Learning and Reasoning (NeSy'13). pp. 7-12, Beijing, August 2013.

 

Heinrich, S., Folleher, P., Springstübe, P., Strahl, E., Twiefel, J., Weber, C., Wermter, S. Object Learning with Natural Language in a Distributed Intelligent System - A Case Study of Human-Robot Interaction. Proceedings of the IEEE First International Conference on Cognitive Systems and Information Processing (CSIP 2012), in press (Springer). Beijing, CN, December 2012.

 

Meins, N., Jirak, D., Weber, C., Wermter, S. Adaboost and Hopfield Neural Networks on Different Image Representations for Robust Face Detection. Proceedings of the 12th International Conference on Hybrid Intelligent Systems (HIS 2012), pp. 531-536, IEEE. Pune, IN, December 2012.

 

Bauer, J., Dávila-Chacón, J., Strahl, E., Wermter, S. Smoke and Mirrors - Virtual Realities for Sensor Fusion Experiments in Biomimetic Robotics. Proceedings of the 2012 IEEE International Conference on Multisensor Fusion and Information Integration (MFI 2012), pp. 114-119, IEEE. Hamburg, DE, September 2012.

 

Heinrich, S., Weber, C., Wermter, S. Adaptive Learning of Linguistic Hierarchy in a Multiple Timescale Recurrent Neural Network. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 555-562, Springer. Lausanne, CH, September 2012.

 

Zhong, J., Weber, C., Wermter, S. Learning Features and Predictive Transformation Encoding Based on a Horizontal Product Model. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 539-546, Springer. Lausanne, CH, September 2012.

 

Meins, N., Wermter, S., Weber, C. Hybrid Ensembles Using Hopfield Neural Networks. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 403-410, Springer Heidelberg. Lausanne, CH, September 2012.

 

Dávila-Chacón, J., Heinrich, S., Liu, J., Wermter, S. Biomimetic Binaural Sound Source Localisation with Ego-Noise Cancellation. Proceedings of the 22nd International Conference on Artificial Neural Networks (ICANN 2012), LNCS 7552, pp. 239-246, Springer. Lausanne, CH, September 2012.

 

Bauer, J., Weber, C., Wermter, S. A SOM-Based Model for Multi-Sensory Integration in the Superior Colliculus. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), pp. 3245-3252, IEEE. Brisbane, AU, June 2012.

 

Yan, W., Weber, C., Wermter, S. A Neural Approach for Robot Navigation based on Cognitive Map Learning. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), pp. 1146-1153, IEEE. Brisbane, AU, June 2012.

 

Navarro, N., Lowe, R., Wermter, S. A neurocomputational amygdala model of auditory fear conditioning: A hybrid system approach. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2012), pp. 214-221, IEEE. Brisbane, AU, June 2012.

 

Zhong, J., Weber, C. Wermter, S. Learning features and transformations with a predictive horizontal product model. Proceedings of the Sixteenth International Conference on Cognitive and Neural Systems (ICCNS 2012), Boston, US, May 2012.

 

Tripathi, N., Oakes, M., Wermter, S. A Fast Subspace Text Categorization Method Using Parallel Classifiers. Proceedings of the 13th International Conference on Computational Linguistics and Intelligent Text Processing (CICLing), LNCS 7182, pp. 132-143, Springer. New Delhi, IN, March 2012.

 

Kleesiek, J., Badde, S., Wermter, S., Engel, A.K. What Do Objects Feel Like? - Active Perception for a Humanoid Robot. Proceedings of the 4th International Conference on Agents and Artificial Intelligence (ICAART 2012), Vol. 1, pp. 64-73, SciTePress. Vilamoura, PT, January 2012.

 

Tripathi, N., Oakes, M., Wermter, S. Hybrid Classifiers for Improved Subspace Learning of News Documents. Proceedings of the 11th International Conference on Hybrid Intelligent Systems (HIS 2011), pp. 28-33, IEEE. Malacca, MY, 2011.

 

Navarro, N., Lowe, R., Weber, C., Wermter, S. Many-routes hypothesis of fear conditioning: a dynamical reservoir based approach. Marie-Curie Researchers Symposium Poster, Warsaw, PL, September 2011.

 

Heinrich, S., Wermter, S. Towards Robust Speech Recognition for Human-Robot Interaction. Proceedings of the IROS2011 Workshop on Cognitive Neuroscience Robotics (CNR), pp. 29-34, San Francisco, CA, USA, September 2011.

 

Zhong, J., Weber, C. Wermter, S. Restricted Boltzmann Machine with Transformation Units in a Mirror Neuron System Architecture. Proceedings of the IROS2011 Workshop on Cognitive Neuroscience Robotics (CNR), pp. 23-28, San Francisco, CA, USA, September 2011.

 

Navarro, N., Weber, W., Wermter, S. Real-world reinforcement learning for autonomous humanoid robot charging in a home environment. Proceedings of the 12th Annual Conference Towards Autonomous Robotic Systems (TAROS 2011), LNCS Vol. 6856, pp. 231-240, Springer Berlin/Heidelberg. Sheffield, UK, August 2011.

 

Kleesiek, J., Weber, C., Wermter, S., Engel, A.K. Reward-Driven Learning of Sensorimotor Laws and Visual Features. Proceedings of the 1st Joint IEEE International Conference on Development and Learning and on Epigenetic Robotics, Vol. 2, pp. 1-6, IEEE. Frankfurt, DE, August 2011.

 

Yan, W., Weber, C., Wermter, S. Person tracking based on a hybrid neural probabilistic model. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), LNCS 6792, Part II, pp. 365-372, Springer. Espoo, FI, June 2011.

 

Zhong, J.P., Weber, C., Wermter S., Robot Trajectory Prediction and Recognition based on a Computational Mirror Neurons Model. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), LNCS 6792, Part II, pp. 333-340, Springer. Espoo, FI, June 2011.

 

Tripathi, N., Oakes, M., Wermter, S. Hybrid Parallel Classifiers for Semantic Subspace Learning. Proceedings of the 21st International Conference on Artificial Neural Networks (ICANN 2011), LNCS 6792, Part II, pp. 64-70, Springer. Espoo, FI, June 2011.

 

Heinrich, S., Eberling, M., Wermter, S. Determining Cooperation in Multiagent Systems with Cultural Traits. Proceedings of the 3rd International Conference on Agents and Artificial Intelligence (ICAART 2011), Vol. 2, pp. 173-180, SciTePress. Rome, IT, January 2011.

 

Knowles, M., Baglee, D., Wermter, S. Reinforcement Learning for Scheduling of Maintenance. Proceedings of the 30th International Conference on Artificial Intelligence (SGAI 2010), pp. 409-422, Springer. Cambridge, England, UK, December 2010.

 

Kleesiek J., Engel A.K., Wermter S., Weber C. Object Affordances in the Context of Sensory Motor Contingencies. Front. Comput. Neurosci. Conference Abstract: Bernstein Conference on Computational Neuroscience, Frontiers. Berlin, DE, September 2010.

 


Yau C. Y., Burn K., Wermter S. Configuring the Stochastic Helmholtz Machine for Subcortical Emotional Learning. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), pp. 1384-1391, IEEE. Barcelona, ES, July 2010.

 

Tripathi N., Wermter S., Hung C., Oakes, M. Semantic Subspace Learning with Conditional Significance Vectors. Proceedings of the International Joint Conference on Neural Networks (IJCNN 2010), pp. 3670-3677, IEEE. Barcelona, ES, July 2010.

 

Anwar, M. N., Oakes, M. P., Wermter, S. and Heinrich, S. Clustering Audiology Data. In Ramon, J., Vens, C., Driessens, K., Van Otterlo, M., Vanschoren, J., editors, Proceedings of the 19th Annual Belgian-Dutch Conference on Machine Learning (BeneLearn 2010), Leuven, BE, May 2010.

 

Liu, J., Perez-Gonzalez, D., Rees, A., Erwin, H. and Wermter, S. Multiple Sound Source Localisation in Reverberant Environments Inspired by the Auditory Midbrain. Artificial Neural Networks -ICANN 2009, Part I, LNCS 5768, pp. 208-217, 2009

 

Liu, J., Perez-Gonzalez, D., Rees, A., Erwin, H. and Wermter, S. A Biomimetic Spiking Neural Network of the Auditory Midbrain for Mobile Robot Sound Localisation in Reverberant Environments. International Joint Conference on Neural Networks (June 2009), pp. 1855-1862, Atlanta, USA.

 

Liu, J., Erwin, H., Wermter, S. Mobile Robot Broadband Sound Localisation Using a Biologically Inspired Spiking Neural Network. IEEE/RSJ International Conference on Intelligent RObots and Systems (IROS 2008). pp. 2191-2196. Nice, France, September, 22-26th, 2008.

 

Liu, J., Erwin, H., Wermter, S. and Elsaid, M. A Biologically Inspired Spiking Neural Network for Sound Localisation by the Inferior Colliculus. Artificial Neural Networks - ICANN 2008, vol. 5164/2008, pp.396-405, August 2008.

 

Murray, J.C, Wermter, S. and Knowles, M.J. MIRA: A Learning Multimodal Interactive Robot Agent. 8th International Conference on Hybrid Intelligent Systems. Barcelona, Spain, September 10-12th, 2008.

 

Knowles, M.J. and Wermter, S. The Hybrid Integration of Perceptual Symbol Systems and Interactive Reinforcement Learning. 8th International Conference on Hybrid Intelligent Systems. Barcelona, Spain, September 10-12th, 2008.

 

Bhagat K.., Wermter, S. and Burn, K. Hybrid Learning Architecture for Unobtrusive Infrared Tracking Support. International Joint Conference on Neural Networks (IJCNN/WCCI), Hongkong, June 2008.

 

Yau, C.Y., Burn, K. and Wermter, S. A Neural Wake-Sleep Learning Architecture for Associating Robotic Facial Emotions. International Joint Conference on Neural Networks (IJCNN/WCCI), Hongkong, June 2008.

 

Altahhan, A., Burn, K. and Wermter, S. Visual Robot Homing using Sarsa, Whole Image Measure, and Radial Basis Function. International Joint Conference on Neural Networks (IJCNN/WCCI), Hongkong, June 2008.

 

Wermter S. Hybrid Intelligent Systems for Cognitive Robotics. International Frontier Science Conference on Experimental Cognitive Robotics, Tokyo/Kanagawa, Japan, 2008. (invited keynote)

 

 
Willmot, C., Wermter S. and Panchev C. Developing Concepts from Robot Behaviour by Growing Self Organizing Networks. 7th International Conference on Epigenetic Robotics, Piscataway, NJ, 2007.

 

Erwin, H., Elshaw, M., Rees, A., Perez-Gonzalez, D., Wermter, S.  Modeling Regular Firing Neurons of the Inferior Colliculus. International Conference on Cognitive Neurodynamics, Shanghai, 2007, pp59-62. (published by Springer in 2008)

 

 
Elshaw, M., Erwin, H., Wermter, S., Perez-Gonzalez,, Rees, A. Modelled properties of single neurons in the auditory midbrain. IBRO World Congress of Neuroscience, Melbourne, Australia, July, 2007.

 

 
Murray, J., Rowan, C., Yau, A., Elshaw, M., Wermter, S. Sound localisation and emotional language communication in the Mira robot head. Proceedings of the AI Video Competition at 22nd AAAI Conference on Artificial Intelligence, Vancouver, July 2007.

 

Hung, C., Chen, J.-H. and Wermter, S. Hybrid Probability-Based Ensembles for Bankruptcy Prediction. International Conference on Business and Information, July 11-13, 2007, Tokyo, Japan.

 

McGarry, K., Garfield S., Wermter S. Auto Extraction, Representation and Integration of a Diabetes Ontology using Bayesian Networks. Proceedings of the IEEE International Symposium on Computer Based Medical Systems.
Maribor, Slovenia, pp. 612-617, 2007.

 

McGarry K., Garfield S., Morris N. and Wermter S. Integration of Hybrid Bio-Ontologies using Bayesian Networks for Knowledge Discovery. In: Artur S. d'Avila Garcez, Pascal Hitzler, Guglielmo Tamburrini (Eds.), Proceedings of the IJCAI-07 Third International Workshop on Neural-Symbolic Learning and Reasoning, NeSy'07, Hyderabad, India, January 2007.

 

Murray J., Wermter S., and Erwin, H. Bioinspired auditory sound localization for improving the signal to noise ratio of socially interactive robots. Proceedings of the International Conference on Intelligent Robots and Systems. pp. 1206-1211. Beijing, China. Oct. 2006.

 

 
Muse D., Burn K., and Wermter S. Reinforcement Learning for Platform-Independent Visual Robot Control. International Joint Conference on Neural Networks, 2006

 

Oakes M P, Cox S. & Wermter S. Data Mining Audiology Records with the Chi-Squared Test and Self-Organising Maps. 22nd British National Conference on Databases. D. Nelson et al. (Eds. ) pp. 123-130, 2005, University of Sunderland Press.

 

Wermter S. Hybrid Intelligent Systems and Cognitive Robotics. Proceedings of the International Conference on Hybrid Intelligent Systems, p. 4, invited keynote talk, Rio de Janeiro, 2005.

 

 
Muse D., Weber C., and Wermter, S. Robot Docking Based on Omnidirectional Vision and Reinforcement Learning. Research and Development in Intelligent Systems XXII - International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 23-36, 2005 Springer.

 

Weber C., Muse D., Elshaw M., and Wermter, S. A Camera-Direction Dependent Visual-Motor Coordinate Transformation for a Visually Guided Neural Robot. Applications and Innovations in Intelligent Systems XIII - International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 151-164, 2005 Springer.

 

Weber C., Karantzis K., and Wermter S. Grasping with flexible viewing-direction with a learned coordinate transformation network. in Proceedings of 5th IEEE-RAS International Conference on Humanoid Robots, pp. 253-258, 2005.

 

Weber W., Wermter S. Image Segmentation by Complex-Valued Units. International Conference on Artificial Neural Networks 2005, pp. 305-310, 2005. Springer.

 

Weber W., Muse D., Elshaw M., Wermter S. Reinforcement Learning in MirrorBot. International Conference on Artificial Neural Networks 2005, pp. 305-310, 2005. Springer.

 

Murray J., Erwin H., Wermter S. Auditory Robotic Tracking of Sound Sources using Hybrid Cross-Correlation and Recurrent Network. International Conference on Intelligent Robots and Systems, 2005.

 

McGarry K., Wermter S. Training without Data: Knowledge Insertion into RBF Neural Networks. International Joint Conference on Artificial Intelligence, Edinburgh, pp. 792-797, 2005.

 

Murray J., Erwin H., Wermter S. A Recurrent Neural Network for Sound-Source Motion Tracking and Prediction. International Joint Conference in Neural Networks, pp. 2232-2236, 2005.

 

Hung C., Wermter S. A Constructive and Hierarchical Self-Organising Model in a Non-Stationary Environment. International Joint Conference in Neural Networks, pp. 2948-2953, 2005.

 

Malone J., Elshaw M., McGarry K., Bowerman C., Wermter S. Spatio-Temporal Neural Data Mining Architecture in Learning Robots. International Joint Conference in Neural Networks, pp. 2802-2807, 2005.

 

Murray J., Erwin H., Wermter S. Robotics Sound-Source Localization and Tracking using Interaural Time Difference and Cross-Correlation. Proceedings of NeuroBotics Workshop, Ulm, Germany, pp. 89-97, September 2004.

 

Elshaw M., Weber C., Zochios A., Wermter S. A Mirror Neuron Inspired Hierarchical Network for Action Selection. Proceedings of NeuroBotics Workshop, Ulm, Germany, pp. 98-105, September 2004.

 

Weber C., Elshaw M., Zochios A., Wermter S. A Multimodal Hierarchical Approach to Robot Learning by Imitation. Fourth International Workshop on Epigenetic Robotics: Modeling Cognitive Development in Robotic Systems, Genoa, Italy, pp. 131-134, 2004.

 

Chokshi K., Panchev C., Wermter S., Burn K. Self Organising Neural Place Codes for Vision Based Robot Navigation. Proceedings of the International Joint Conference on Neural Networks, Budapest, Hungary, pp. 2501-2506, July 2004.

 

Chokshi K., Panchev C., Wermter S., Taylor J. Knowing What and Where: A Computational Model for Visual Attention. Proceedings of the International Joint Conference on Neural Networks, pp. 519-524, Budapest, Hungary, July 2004.

 

Elshaw M., Weber C., Zochios A., Wermter S. An Associator Network Approach to Robot Learning by Imitation through Vision, Motor Control and Language.  Proceedings of the International Joint Conference on Neural Networks, pp. 591-596, Budapest, Hungary, July 2004.

 

Hung C., Wermter S. A Time-Based Self-Organising Model for Document Clustering.   Proceedings of the International Joint Conference on Neural Networks, pp. 17-23, Budapest, Hungary, July 2004.

 

Hung C., Wermter S., Smith P. Predictive Top-down Knowledge Improves Neural Exploratory Bottom-up Clustering. Proceedings of ECIR’04 European Conference on Information Retrieval, Sunderland, UK, pp. 154-166, 5-7, April 2004.

 

Addison J.  McGarry K. Wermter S. MacIntyre J.  Stepwise Linear Regression Dimensionality Reduction in Neural Network Modelling. Proceedings of the International Conference on Artificial Intelligence and Applications, pp. 363-368, Innsbruck, Austria, February 2004.

 

Panchev C., Wermter S. Spiking-time-dependent Synaptic Plasticity: From Single Spikes to Spike Trains. Proceedings of the Computational Neuroscience Meeting, Alicante, Spain, July 2003.

 

Hung C., Wermter S. A Self-Organising Hybrid Model for Dynamic Text Clustering. Proceedings of the The Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK, December, pp. 141-154 2003.

 

Hung C., Wermter S., A Dynamic Adaptive Self-Organising Hybrid Model for Text Clustering. Proceedings of The Third IEEE International Conference on Data Mining, pp. 75-82, Melbourne, USA, 2003.

 

Wermter S., Elshaw M., Weber C., Panchev C., Erwin  H. Towards Integrating Learning by Demonstration and Learning by Instruction in a Multimodal Robotics. Proceedings of the IROS-2003 Workshop on Robot Learning by Demonstration, pp. 72-79, Las Vegas, USA, October 2003.

 

Weber C., Wermter S., Zochios A. Robot Docking with Neural Vision and Reinforcement. Proceedings of the Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK, December 2003.

 

Elshaw M., Lewis D., Wermter S. Incorporating Reactive Learning Behaviour into a Mini-robot Platform. Proceedings of the Twenty-third SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, Cambridge, UK, December, pp. 255-266, 2003.

 

Garfield, S., Wermter S. Comparing State Vector Machines, Recurrent Networks and Finite State Transducers for Classifying Spoken Utterances. International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 646-653, June 2003.

 

Weber C., Wermter S. Object Localisation using Laterally Connected What and Where Associator Networks. Proceedings of the International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 813-820, June 2003.

 

Addison D., Wermter S., Arevian G. A Comparison of Feature Extraction and Selection Techniques. Proceedings of the International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 212-215, June 2003.

 

Chokshi K., Wermter S., Weber C. Learning Localisation Based on Landmarks using Self-Organisation. Proceedings of the International Conference on Artificial Neural Networks, Istanbul, Turkey, pp. 505-511, June 2003.

 

Elshaw M., Wermter S., Watt P. Self-organisation of Language Instruction for Robot Action. Proceedings of the International Joint Conference on Neural Networks. Oregon, USA, pp. 22-27, July 2003.

 

Garfield S., Wermter S. Recurrent Neural Learning for Helpdesk Call Routing. Proceedings of the International Conference on Artificial Neural Networks, Madrid, Spain, pp. 296-301, August 2002.

 

Wermter S., Hung C. Selforganizing Classification on the New Reuters News Corpus. Proceedings of the International Conference on Computational Linguistics, Taipei, Taiwan, pp.1086-1092, August 2002.

 

Addison D., Wermter S., McGarry K., Macintyre J. Methods for Integrating Memory into Neural Networks in Condition Monitoring. Proceedings of the International Conference on Artificial Intelligence and Soft Computing, Banff, Alberta, Canada, pp. 380-384, July 2002.

 

Panchev C., Wermter S., Chen H. Spike-timing Dependant Competitive Learning of Integrate-and-Fire Neurons with Active Dendrites. Proceedings of the International Conference on Artificial Neural Networks, pp. 896-901, August 2002.

 

Womble S., Wermter S. and Treves A. Information Processing in Layer 4: A Tabula Rasa? Proceedings of the Sixth International Conference on Cognitive and Neural Systems, May 2002.

 

 
Elshaw, M., Wermter S. A Neurocognitive Approach to Self-organisation of Verb Actions. Proceedings of the International Joint Conference on Neural Networks. Honolulu, USA, pp. 24-29, May 2002.

 

Panchev C., Wermter S. Hebbian Spike-Timing Dependent Self-Organization in Pulse Neural Networks. Proceedings of World Congress on Neuroinformatics. Vienna, Austria, pp. 378-385, September 2001.

 

Addison D., Wermter S., and Macintyre J. Multilayer Perceptrons and Radial Basis Function Networks for Corrosion Monitoring. Proceedings of the International Conference on Artificial Intelligence and Applications . Marbella, September 2001, pp. 77-81.

 

Womble S., Wermter S. A Mirror Neuron System for Syntax Acquisition. Proceedings of International Conference on Artificial Neural Networks. Vienna, Austria, August 2001, pp.1213-1219.

 

Garfield S., Elshaw M., Wermter S. Self-Organising Networks for Classification Learning from Normal and Aphasic Speech. Proceedings of the 23rd Conference of the Cogntive Science Society. Edinburgh, Scotland, August 2001, pp. 319-324.

 

McGarry K., Wermter S., Macintyre, J. Knowledge Extraction from Local Function Networks. Proceedings of the International Joint Conference on Artificial Intelligence. Seattle, August 4-10, p. 765-771, 2001.

 

Wermter S., Arevian G. Modular Preference Moore Machines in News Mining Agents. Proceedings of the Joint 9th International Fuzzy Systems Association World Congress and the 20th North American Fuzzy Information Processing Society International Conference. Vancouver, Canada, pp. 1786-1792, July 2001.

 

Wermter S., Austin J., Willshaw D. Proceedings of the International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience, Durham, UK, 7-8 August 2000.

 

 
Panchev C., Wermter S. Sequential Processing in Neuroscience Inspired Models. Proceedings of Third International Workshop on Current Computational Architectures Integrating Neural Networks and Neuroscience. p. 84-88. Durham, UK, August 2000.

 

Wermter S., Panchev C. Hybrid Sequential Machines based on Neuroscience. Proceedings of the ECAI Workshop on Foundations of Connectionist Symbolic Integration. p. 13-24. Berlin, Germany, August 2000.

 

Wermter S., Arevian, G., Panchev C. Meaning Spotting and Robustness of Recurrent Networks. Proceedings of the International Joint Conference on Neural Networks. p. III-433-438. Como, Italy, July 2000.

 

Panchev C., Wermter S. Complex Preferences for the Integration of Neural Codes. Proceedings of the International Joint Conference on Neural Networks. p. III-433-258. Como, Italy, July 2000.

 

Womble S., Wermter S. Language Acquisition in the Brain Using Reinforcement Learning Agents. Proceedings of the International Conference on Mirror Neurons and the Evolution of Brain and Language. Delmenhorst, Germany, July 2000.

 

Wermter S., Arevian, G., Panchev, C. Network Analysis in a Neural Learning Internet Agents. Proceedings of the International Conference on Computer Intelligence and Neuroscience. p. 880-884, Atlantic City, USA, March 2000.

 

Wermter S., Austin J., Willshaw D. Proceedings of International Workshop on Emergent Neural Computational Architectures Based on Neuroscience. Edinburgh, UK, 11 September 1999.

 

 
McGarry K., Tait J., Wermter S., MacIntyre J. Rule Extraction from Radial Basis Function Networks. Proceedings of the International Conference on Artificial Neural Networks. p. 613-618, Edinburgh, UK, September 1999.

 

 
Wermter S., Arevian G., Panchev C. Recurrent Neural Network Learning for Text Routing. Proceedings of the International Conference on Artificial Neural Networks. p. 898-903, Edinburgh, UK, September 1999.

 

Addison D., Wermter S., MacIntyre J. Effectiveness of Feature Extraction in Neural Network Architectures for Novelty Detection. Proceedings of the International Conference on Artificial Neural Networks. p. 976-981, Edinburgh, UK, September 1999.

 

Wermter S. Preference Moore Machines for Neural Fuzzy Integration. Proceedings of the International Joint Conference on Artificial Intelligence. p. 840-845, Stockholm, Sweden, August 1999.

 

Wermter S., Austin J., Willshaw D. Proceedings of the Workshop on Neuroscience and Neural Computation. Orlando, Florida, USA, 19 July 1999.

 

 
Wermter S., Panchev C., Houlsby J. Language Disorders in the Brain: Distinguishing Aphasia Forms with Recurrent Networks. Proceedings of AAAI*99 Conference Workshop on Neuroscience and Neural Computation. p. 93-98, Orlando, USA, July 1999.

 

McAlister M., Wermter S. Rule Generation from Neural Networks for Student Assessment. Proceedings of the International Joint Conference on Neural Networks, Washington, USA, July 1999.

 

 
McGarry K., Wermter S., MacIntyre J. Knowledge Extraction from Radial Basis Function Networks and Multi-layer Perceptrons. Proceedings of the International Joint Conference on Neural Networks. Washington, USA, July 1999.

 

Wermter S., Panchev C. Arevian G. Hybrid Neural Plausibility Networks for News Agents. Proceedings of the National Conference on Artificial Intelligence. AAAI. p. 93-98, Orlando, USA, July 1999.

 

McGarry K., Wermter S., MacIntyre J. Knowledge Transfer Between Radical Basis Function Networks. Proceedings of Conference on Cognitive Science for the New Millennium. Dublin, Ireland, May 1999.

 

 
Wermter S., Sun R. Proceedings of the Nips Workshop on Hybrid Neural Symbolic Integration. Breckenridge, Colorado, USA, 1998.

 

 
Wermter S. Lazy Neural Network Learning for Building Symbolic Transducers. Proceedings of the International Conference on Computational Intelligence and Neuroscience. Research Triangle Park, North Carolina, USA, 1998.

 

 
Wermter S. Hybrid Neural Symbolic Agent Architectures for Multimedia. Proceedings of the IEE Colloquium on Neural Network in Interactive Multimedia Systems. London, 1998.

 

 
Chen J., Wermter S. Continuous Time Recurrent Neural Networks for Grammatical Induction. Proceedings of the International Conference on Artificial Neural Networks. p. 381-386, Skovde, Sweden, 1998.

 

Wermter S. Hybrid Neural and Symbolic Language Processing. Proceedings of the Interdisciplinary Conference. Guenne, Germany, 1998.

 

 
Busemann S., Harbusch K., Wermter S. Proceedings of the Workshop on Hybrid Connectionist, Statistical and Symbolic Approaches to Language Processing. DFKI, 1998-3. Freiburg, 1998.

 

 
Wermter S. Hybrid Approaches to Neural Network-based Language Processing. International Computer Science Institute. Berkeley, CA, 1997, TR-97-030

 

Wermter S., Meurer M. Building Lexical Representations Dynamically Using Artificial Neural Networks. Proceedings of the International Conference of the Cognitive Science Society. p. 802-807, Stanford, 1997.

 

Wermter S., Chen J. Cautious Steps towards Hybrid Connectionist Bilingual Phrase Alignment. Proceedings of the Conference on Recent Advances in Natural Language Processing. p. 364-368, Sofia, Bulgaria, 1997.

 

 
Wermter S., Löchel M. Learning Dialog Act Processing. Proceedings of the International Conference on Computational Linguistics. p. 740-745, Kopenhagen, Denmark, 1996.

 

Wermter S., Meurer M. Towards Constructive and Destructive Dynamic Network Configuration. Proceedings of the European Symposium on Artificial Neural Networks. Brugge, Belgium, 1996.

 

 
Wermter S., Weber V. Artificial Neural Networks for Automatic Knowledge Acquisition in Multiple Real-World Language Domains. In Proceedings of the 8th International Conference on Neural Networks and their Applications. p. 289-296, Marseilles, FRA, 1995.

 

Weber V., Wermter S. Artificial Neural Networks for Repairing Language. In Proceedings of the 8th International Conference on Neural Networks and their Applications. Marseilles, France, 1995.

 

Wermter S., Weber V. Learning Fault-Tolerant Speech Parsing with SCREEN. In Twelfth National Conference on Artificial Intelligence. p. 670-675, Seattle, Washington, July/August 1994.

 

Wermter S., Löchel M. Connectionist learning of flat syntactic analysis for speech/language systems. Proceedings of the International Conference on Artificial Neural Networks. p. 941-944, Sorrento, Italy, 1994.

 

 
Wermter S. Learning Natural Language Filtering Under Noisy Conditions. Proceedings of the Tenth IEEE Conference on Artificial Intelligence for Applications. p. 215-221, San Antonio, USA, 1994.

 

 

Wermter S., Lehnert W. G. A Parallel Model for Compositional Similarity of Natural Language Concepts. In: Hahn U., Adriaens G. (Eds.) Parallel Natural Language Processing. pp. 376-394, Ablex Publishers, Norwood, NJ, 1994.

 

 
Wermter S. Hybride Symbolische und Subsymbolische Verarbeitung am Beispiel der Sprachverarbeitung. In: Duwe I., Kurfess F., Paass G., Vogel S. (Eds.) Proceedings of the Herbstschule Konnektionismus und Neuronale Netze. GMD, Sankt Augustin, 1994.

 

 
Wermter S., Peters U. Learning Incremental Case Assignments Based on Modular Connectionist Knowledge Sources. Proceedings of the World Congress on Neural Networks, p. 538-543, San Diego, USA, 1994.

 

 
Wermter S. 1993. Connectionist Context Processing for Phrase Filtering. Proceedings of the World Congress on Neural Networks. p. 100-103, Portland, USA.

 

 
Wermter S. 1992. SCANing Understanding: A Hybrid and Connectionist Architecture. Proceedings of the AAAI Workshop on Integrating Neural and Symbolic Processes. p. 83-90, San Jose, USA.

 

 
Wermter S. 1992. Learning a Scanning Understanding for "Real-world" Library Categorization. Proceedings of the Conference on Applied Natural Language Processing. p. 251-252, Trento, Italy.

 

 
Wermter S. 1992. A Hybrid and Connectionist Architecture for a SCANning Understanding. In: Neumann, B. (Eds.) Proceedings of the 10th European Conference on Artificial Intelligence. p. 188-192, Vienna, Austria.

 

Wermter S. 1991. Learning to Classify Natural Language Titles in a Recurrent Connectionist Model. Proceedings of the International Conference on Artificial Neural Networks. p. II 1715-1718, Espoo, Finland.

 

 
Wermter S. 1991. Learning the Work of a Librarian: a Connectionist Model for Semantic Classification. Proceedings of the AAAI Spring Symposium on Connectionist Natural Language Processing. p. 72-77, Stanford, USA.

 

 
Wermter S. 1991. Learning and Representing Natural Language Phrases in a Hybrid Symbolic/Connectionist Approach. Proceedings of the AAAI Spring Symposium on Machine Learning of Natural Language and Ontology. p. 191-195, Stanford, CA, USA.

 

 
Wermter S. 1990. Combining Symbolic and Connectionist Techniques for Coordination in Natural Language. Marburger H. (Ed.) Proceedings of the 14th German Workshop on Artificial Intelligence, p. 186-195, Schloss Eringerfeld, FRG.

 

 
Wermter S. 1989. Learning Semantic Relationships in Compound Nouns with Connectionist Networks. Proceedings of the Eleventh Conference of the Cognitive Science Society. p. 964-971, Ann Arbor, MI, USA.

 

Wermter S. 1989. Integration of Semantic and Syntactic Constraints for Structural Noun Phrase Disambiguation. Proceedings of the Eleventh International Joint Conference on Artificial Intelligence. p. 1486-1491, Detroit, USA.