Lukas Muttenthaler 个人学术档案

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	总计	2019 年至今
引用	184	184
h 指数	8	8
i10 指数	8	8

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Martin N. HebartJustus Liebig University, Giessen, Germany在 psychiat.med.uni-giessen.de 的电子邮件经过验证
Robert A. VandermeulenTechnische Universität Berlin & BIFOLD在 tu-berlin.de 的电子邮件经过验证
Simon KornblithAnthropic在 anthropic.com 的电子邮件经过验证
Lorenz LinhardtTU Berlin在 campus.tu-berlin.de 的电子邮件经过验证
Francisco PereiraMachine Learning Team, National Institute of Mental Health在 nih.gov 的电子邮件经过验证
Katherine L. HermannGoogle DeepMind在 stanford.edu 的电子邮件经过验证
Hugo Andrés LópezAssociate Professor, Technical University of Denmark在 dtu.dk 的电子邮件经过验证
Maria BarrettPost doc, IT University of Copenhagen在 itu.dk 的电子邮件经过验证
Nora HollensteinUniversity of Zurich在 uzh.ch 的电子邮件经过验证
Patrick McClureMachine Learning Team, National Institute of Mental Health在 nih.gov 的电子邮件经过验证
Charles Yang ZhengNational Institute of Mental Health在 nih.gov 的电子邮件经过验证
Andrew Kyle LampinenResearch Scientist, DeepMind在 google.com 的电子邮件经过验证
Johannes BjervaAssociate Professor, Department of Computer Science, Aalborg University在 cs.aau.dk 的电子邮件经过验证
Isabelle AugensteinFull Professor, Department of Computer Science, University of Copenhagen在 di.ku.dk 的电子邮件经过验证
Ulrich AnsorgeProfessor of Cognitive Psychology, University of Vienna在 univie.ac.at 的电子邮件经过验证
Thomas UnterthinerGoogle DeepMind在 pm.me 的电子邮件经过验证
Klaus-Robert MüllerGoogle DeepMind & TU Berlin & Korea University & Max Planck Institute for Informatics, Germany在 tu-berlin.de 的电子邮件经过验证
Umut GüçlüPrincipal Investigator, Donders Institute for Brain, Cognition and Behaviour在 donders.ru.nl 的电子邮件经过验证

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Lukas Muttenthaler

TU Berlin & Google DeepMind & Max-Planck-Institute for Human Cognitive and Brain Sciences

在 tu-berlin.de 的电子邮件经过验证 - 首页

Machine Learning Representation Learning AI Alignment Computer Vision Cognitive Science


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Human alignment of neural network representations L Muttenthaler, J Dippel, L Linhardt, RA Vandermeulen, S Kornblith International Conference on Learning Representations (ICLR) 11, 2023	31	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	31	2021
Authorship Attribution in Fan-Fictional Texts given variable length Character and Word N-Grams L Muttenthaler, G Lucas, J Amann CEUR Workshop Proceedings, 2019	25*	2019
Getting aligned on representational alignment I Sucholutsky, L Muttenthaler, A Weller, A Peng, A Bobu, B Kim, ... arXiv preprint arXiv:2310.13018, 2023	22	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	20	2019
Human brain activity for machine attention L Muttenthaler, N Hollenstein, M Barrett arXiv preprint arXiv:2006.05113, 2020	17	2020
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	15	2023
VICE: Variational Interpretable Concept Embeddings L Muttenthaler, CY Zheng, P McClure, RA Vandermeulen, MN Hebart, ... Advances in Neural Information Processing Systems (NeurIPS) 35, 2022	15	2022
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
A Novel Test of Pure Irrelevance-Induced Blindness C Büsel, T Ditye, L Muttenthaler, U Ansorge Frontiers in Psychology 10, 375, 2019	1	2019
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		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
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		2022
Effective enhancement of attentional functions in the amblyopic brain. L Muttenthaler Journal of European Psychology Students 10 (1), 2019		2019
First Workshop on Representational Alignment (Re-Align) E Grant, I Sucholutsky, J Achterberg, K Hermann, L Muttenthaler ICLR 2024 Workshops, 0
Compositional Skills of Recurrent Neural Networks L Muttenthaler

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