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Adapting the 2-Class Recursive Deterministic Perceptron Neural Network to m Classes, M. Tajine, D. Elizondo, Emile Fiesler and Jerzy Korczak, in: Proceedings of the International Conference on Neural Networks, IEEE, IEEE, 1997
Joint estimation of RETF vector and power spectral densities for speech enhancement based on alternating least squares, Marvin Tammen, Ina Kodrasi and Simon Doclo, in: IEEE International Conference on Acoustics, Speech and Signal Processing, pages 795--799, 2019
Complexity reduction of eigenvalue decomposition-based diffuse power spectral density estimators using the power method, Marvin Tammen, Ina Kodrasi and Simon Doclo, in: Proc. International Conference on Acoustics, Speech, and Signal Processing, Calgary, Canada, pages 451-455, 2018
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Iterative alternating least-aquares approach to jointly estimate the RETFs and the diffuse PSD, Marvin Tammen, Ina Kodrasi and Simon Doclo, in: Proc. ITG conference on Speech Communication, Oldenburg, Germany, 2018
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On the Language-specificity of Multilingual BERT and the Impact of Fine-tuning, Marc Tanti, Lonneke van der Plas, Claudia Borg and Albert Gatt, in: Proceedings of the Fourth BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP, 2021
Small Variance Asymptotics for Non-Parametric Online Robot Learning, A. K. Tanwani and Sylvain Calinon, in: International Journal of Robotics Research (IJRR), 38(1):3-22, 2019
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Sequential Robot Imitation Learning from Observations, A. K. Tanwani, A. Yan, J. Lee, Sylvain Calinon and K. Goldberg, in: International Journal of Robotics Research (IJRR), 2021
Transfer in Inverse Reinforcement Learning for Multiple Strategies, Ajay Kumar Tanwani and Aude Billard, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, Tokyo, Japan, pages 3244-3250, IEEE, 2013
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A Generative Model for Intention Recognition and Manipulation Assistance in Teleoperation, Ajay Kumar Tanwani and Sylvain Calinon, in: IEEE/RSJ International Conference on Intelligent Robots and Systems, 2017
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Online Inference in Bayesian Non-Parametric Mixture Models under Small Variance Asymptotics, Ajay Kumar Tanwani and Sylvain Calinon, in: NIPS workshop on Advances in Approximate Bayesian Inference, Barcelona, Spain, pages 1-5, 2016
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Rewards-driven control of robot arm by decoding EEG signals, Ajay Kumar Tanwani, José del R. Millán and Aude Billard, in: Engineering in Medicine and Biology Society (EMBC), 2014 36th Annual International Conference of the IEEE, pages 1658-1661, IEEE, 2014
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Towards Accessible Sign Language Learning and Assessment, Neha Tarigopula, Sandrine Tornay, Skanda Muralidhar and Mathew Magimai.-Doss, in: ACM International Conference on Multimodal Interaction, Bangalore, INDIA, pages 626-631, 2022
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Time-Sensitive Topic Models for Action Recognition in Videos, Romain Tavenard, Remi Emonet and Jean-Marc Odobez, in: IEEE International Conference on Image Processing, 2013
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Unshuffling data for improved generalization in visual question answering, Damien Teney, Ehsan Abbasnejad and Anton van den Hengel, in: Proceedings of the IEEE/CVF International Conference on Computer Vision, 2021
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A Differentiable Integer Linear Programming Solver for Explanation-Based Natural Language Inference, Mokanarangan Thayaparan, Marco Valentino and Andre Freitas, in: The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, 2024
Explainable Inference Over Grounding-Abstract Chains for Science Questions, Mokanarangan Thayaparan, Marco Valentino and Andre Freitas, in: 59th Annual Meeting of the Association for Computational Linguistics (ACL Findings), 2021
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Imposing Relation Structure in Language-Model Embeddings Using Contrastive Learning, Christos Theodoropoulos, James Henderson, Andrei Catalin Coman and Marie-Francine Moens, in: Proceedings of the 25th Conference on Computational Natural Language Learning, Online, pages 337-348, Association for Computational Linguistics, 2021
Tracking Articulators in X-ray Movies of the Vocal Tract, Georg Thimm, in: 8th Int. Conf. Computer Analysis of Images and Patterns, Springer Verlag, 1999
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Optimization of high order perceptrons, Georg Thimm, École Polytechnique Fédérale de Lausanne, 1997
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Evaluating the Complexity of Databases for Person Identification and Verification, Georg Thimm, Souheil Ben-Yacoub and Juergen Luettin, in: 8th Int. Conf. Computer Analysis of Images and Patterns, Springer Verlag, 1999
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High Order and Multilayer Perceptron Initialization, Georg Thimm and Emile Fiesler, in: IEEE Transactions on Neural Networks, 8(02), 1997
Two neural network construction methods, Georg Thimm and Emile Fiesler, in: Neural Processing Letters, 6(01), 1997
A Boolean Approach to Construct Neural Networks for Non-Boolean Problems, Georg Thimm and Emile Fiesler, in: Proceedings of the 8th IEEE International Conference on Tools with Artificial Intelligence, IEEE, 1996
Evaluating pruning methods, Georg Thimm and Emile Fiesler, in: 1995 International Symposium on Artificial Neural Networks (ISANN'95), 1995
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Weight Initialization for High Order and Multilayer Perceptrons, Georg Thimm and Emile Fiesler, in: Proceedings of the '94 SIPAR--Workshop on Parallel and Distributed Computing, SI Group for Parallel Systems, 1994
Neural Network Pruning and Pruning Parameters, Georg Thimm and Emile Fiesler, in: The 1st Workshop on Soft Computing, Dept. of Information Electronics Nagoya University, 1996
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Neural Network Initialization, Georg Thimm and Emile Fiesler, in: From Natural to Artificial Neural Computation, Springer Verlag, 1995
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