| Human alignment of neural network representations L Muttenthaler, J Dippel, L Linhardt, RA Vandermeulen, S Kornblith International Conference on Learning Representations (ICLR) 11, 2023 | 44 | 2023 |
| THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks L Muttenthaler, MN Hebart Frontiers in Neuroinformatics 15, 45, 2021 | 38 | 2021 |
| Getting aligned on representational alignment I Sucholutsky*, L Muttenthaler*, A Weller, A Peng, A Bobu, B Kim, ... arXiv preprint arXiv:2310.13018, 2023 | 36* | 2023 |
| Authorship Attribution in Fan-Fictional Texts given variable length Character and Word N-Grams L Muttenthaler, G Lucas, J Amann CEUR Workshop Proceedings, 2019 | 27* | 2019 |
| Improving neural network representations using human similarity judgments L Muttenthaler, L Linhardt, J Dippel, RA Vandermeulen, K Hermann, ... Advances in Neural Information Processing Systems (NeurIPS) 36, 2023 | 20 | 2023 |
| Assisted declarative process creation from natural language descriptions HA López, M Marquard, L Muttenthaler, R Strømsted 2019 IEEE 23rd International Enterprise Distributed Object Computing …, 2019 | 19 | 2019 |
| VICE: Variational Interpretable Concept Embeddings L Muttenthaler, CY Zheng, P McClure, RA Vandermeulen, MN Hebart, ... Advances in Neural Information Processing Systems (NeurIPS) 35, 2022 | 18 | 2022 |
| Human brain activity for machine attention L Muttenthaler, N Hollenstein, M Barrett arXiv preprint arXiv:2006.05113, 2020 | 17 | 2020 |
| Unsupervised Evaluation for Question Answering with Transformers L Muttenthaler, I Augenstein, J Bjerva Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting …, 2020 | 5 | 2020 |
| Subjective Question Answering: Deciphering the inner workings of Transformers in the realm of subjectivity L Muttenthaler arXiv preprint arXiv:2006.08342, 2020 | 2 | 2020 |
| Dimensions underlying the representational alignment of deep neural networks with humans FP Mahner*, L Muttenthaler*, U Güçlü, MN Hebart arXiv preprint arXiv:2406.19087, 2024 | 1 | 2024 |
| Set Learning for Accurate and Calibrated Models L Muttenthaler*, RA Vandermeulen*, Q Zhang, T Unterthiner, KR Müller International Conference on Learning Representations (ICLR) 12, 2024 | 1 | 2024 |
| Interpretable object dimensions in deep neural networks and their similarities to human representations L Muttenthaler, MN Hebart Oral @ 22nd Annual Meeting of the Vision Sciences Society (VSS 2022) 22 (14 …, 2022 | 1 | 2022 |
| A Novel Test of Pure Irrelevance-Induced Blindness C Büsel, T Ditye, L Muttenthaler, U Ansorge Frontiers in Psychology 10, 375, 2019 | 1 | 2019 |
| Evaluating and supervising vision models with multi-level similarity judgments F Born*, L Muttenthaler*, K Greff, T Unterthiner, AK Lampinen, KR Müller, ... Conference on Cognitive Computational Neuroscience (CCN 2024), 2024 | | 2024 |
| First Workshop on Representational Alignment (Re-Align) E Grant, I Sucholutsky, J Achterberg, K Hermann, L Muttenthaler ICLR 2024 Workshops, 2024 | | 2024 |
| Dimensions That Matter – Interpretable Object Dimensions in Humans and Deep Neural Networks FP Mahner*, L Muttenthaler*, U Güçlü, MN Hebart Conference on Cognitive Computational Neuroscience (CCN 2023), 2023 | | 2023 |
| Effective enhancement of attentional functions in the amblyopic brain L Muttenthaler Journal of European Psychology Students 10 (1), 1-10, 2019 | | 2019 |
| Compositional Skills of Recurrent Neural Networks L Muttenthaler | | |
Martin N. HebartJustus Liebig University, Giessen, Germany在 psychiat.med.uni-giessen.de 的电子邮件经过验证
