| Investigation of activation functions for generalized learning vector quantization T Villmann, J Ravichandran, A Villmann, D Nebel, M Kaden Advances in Self-Organizing Maps, Learning Vector Quantization, Clustering …, 2020 | 21 | 2020 |
| Quantum-inspired learning vector quantizers for prototype-based classification: Confidential: for personal use only—submitted to Neural Networks and Applications 5/2020 T Villmann, A Engelsberger, J Ravichandran, A Villmann, M Kaden Neural Computing and Applications 34 (1), 79-88, 2022 | 20 | 2022 |
| Variants of dropconnect in learning vector quantization networks for evaluation of classification stability J Ravichandran, M Kaden, S Saralajew, T Villmann Neurocomputing 403, 121-132, 2020 | 16 | 2020 |
| Quantum-Inspired Learning Vector Quantization for Classification Learning T Villmann, J Ravichandran, A Engelsberger, A Villmann, M Kaden Proceedings of the 28th European Symposium on Artificial Neural Networks …, 2020 | 7 | 2020 |
| Variants of recurrent learning vector quantization J Ravichandran, M Kaden, T Villmann Neurocomputing 502, 27-36, 2022 | 6 | 2022 |
| A learning vector quantization architecture for transfer learning based classification in case of multiple sources by means of null-space evaluation T Villmann, D Staps, J Ravichandran, S Saralajew, M Biehl, M Kaden International Symposium on Intelligent Data Analysis, 354-364, 2022 | 6 | 2022 |
| Activation functions for generalized learning vector quantization-a performance comparison T Villmann, J Ravichandran, A Villmann, D Nebel, M Kaden arXiv preprint arXiv:1901.05995, 2019 | 4 | 2019 |
| DropConnect for Evaluation of Classification Stability in Learning Vector Quantization. J Ravichandran, S Saralajew, T Villmann ESANN, 2019 | 2 | 2019 |
| Dropout in learning vector quantization networks for regularized learning and classification confidence estimation T Villmann, JRD Ravichandran, S Saralajew, M Biehl Mittweida Workshop on Computational Intelligence, 2018 | 1 | 2018 |
| Trustworthiness and Confidence of Gait Phase Predictions in Changing Environments Using Interpretable Classifier Models D Möbius, J Ravichandran, M Kaden, T Villmann International Conference on Neural Information Processing, 379-390, 2022 | | 2022 |
| RecLVQ: Recurrent Learning Vector Quantization. J Ravichandran, T Villmann, M Kaden ESANN, 2021 | | 2021 |
| Recurrent Learning Vector Quantization J Ravichandran, T Villmann 26. Interdisziplinäre Wissenschaftliche Konferenz Mittweida, 147-148, 2021 | | 2021 |
| DropConnect in LVQ networks for regularization and confidence interval estimation J Ravichandran, JR Dinesh | | 2018 |
| 1331-Abstract not received J Ravichandran, T Villmann, MS Gumisiriza, ER Mbega Proceedings of the Seventh International Congress of Pharmacology, 520, 1978 | | 1978 |
Thomas VillmannProfessor for Mathematics and Computational Intelligence, University of Applied Sciences Mittweida在 hs-mittweida.de 的电子邮件经过验证
