Követés
Lukas Muttenthaler
Lukas Muttenthaler
TU Berlin & Google DeepMind
E-mail megerősítve itt: tu-berlin.de - Kezdőlap
Cím
Hivatkozott rá
Hivatkozott rá
Év
Getting aligned on representational alignment
I Sucholutsky*, L Muttenthaler*, A Weller, A Peng, A Bobu, B Kim, ...
arXiv preprint arXiv:2310.13018, 2023
84*2023
Human alignment of neural network representations
L Muttenthaler, J Dippel, L Linhardt, RA Vandermeulen, S Kornblith
International Conference on Learning Representations (ICLR) 11, 2023
622023
THINGSvision: A Python Toolbox for Streamlining the Extraction of Activations From Deep Neural Networks
L Muttenthaler, MN Hebart
Frontiers in Neuroinformatics 15, 45, 2021
462021
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
312023
Authorship Attribution in Fan-Fictional Texts given variable length Character and Word N-Grams
L Muttenthaler, G Lucas, J Amann
CEUR Workshop Proceedings, 2019
29*2019
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
242019
VICE: Variational Interpretable Concept Embeddings
L Muttenthaler, CY Zheng, P McClure, RA Vandermeulen, MN Hebart, ...
Advances in Neural Information Processing Systems (NeurIPS) 35, 2022
212022
Human brain activity for machine attention
L Muttenthaler, N Hollenstein, M Barrett
arXiv preprint arXiv:2006.05113, 2020
192020
Unsupervised Evaluation for Question Answering with Transformers
L Muttenthaler, I Augenstein, J Bjerva
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting …, 2020
62020
Aligning Machine and Human Visual Representations across Abstraction Levels
L Muttenthaler, K Greff, F Born, B Spitzer, S Kornblith, MC Mozer, ...
arXiv preprint arXiv:2409.06509, 2024
4*2024
Subjective Question Answering: Deciphering the inner workings of Transformers in the realm of subjectivity
L Muttenthaler
arXiv preprint arXiv:2006.08342, 2020
32020
When Does Perceptual Alignment Benefit Vision Representations?
S Sundaram, S Fu, L Muttenthaler, NY Tamir, L Chai, S Kornblith, ...
Advances in Neural Information Processing Systems (NeurIPS) 37, 2024
22024
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
22024
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
12024
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
12024
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
12022
A Novel Test of Pure Irrelevance-Induced Blindness
C Büsel, T Ditye, L Muttenthaler, U Ansorge
Frontiers in Psychology 10, 375, 2019
12019
Training objective drives the consistency of representational similarity across datasets
L Ciernik, L Linhardt, M Morik, J Dippel, S Kornblith, L Muttenthaler
arXiv preprint arXiv:2411.05561, 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
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