Title
When Does Closeness in Distribution Imply Representational Similarity? An Identifiability Perspective Beatrix M. G. Nielsen Emanuele Marconato Andrea Dittadi Luigi Gresele 58 0 0 04 Jun 2025
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The Origins of Representation Manifolds in Large Language Models Alexander Modell Patrick Rubin-Delanchy N. Whiteley MILM AI4CE 33 0 0 23 May 2025
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Mind the Gap: Bridging the Divide Between AI Aspirations and the Reality of Autonomous Characterization Grace Guinan Addison Salvador Michelle A. Smeaton Andrew Glaws Hilary Egan Brian C. Wyatt Babak Anasori K. Fiedler M. Olszta Steven Spurgeon 124 0 0 25 Feb 2025
Formation of Representations in Neural Networks Liu Ziyin Isaac Chuang Tomer Galanti T. Poggio 247 7 0 03 Oct 2024
InfoNCE: Identifying the Gap Between Theory and Practice E. Rusak Patrik Reizinger Attila Juhos Oliver Bringmann Roland S. Zimmermann Wieland Brendel 133 11 0 28 Jun 2024
Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations? Mark Ibrahim David Klindt Randall Balestriero SSL 130 5 1 15 Jun 2024
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The Linear Representation Hypothesis and the Geometry of Large Language Models Kiho Park Yo Joong Choe Victor Veitch LLMSV MILM 176 190 0 07 Nov 2023
Identifiable Contrastive Learning with Automatic Feature Importance Discovery Qi Zhang Yifei Wang Yisen Wang 72 13 0 29 Oct 2023
Leveraging sparse and shared feature activations for disentangled representation learning Marco Fumero F. Wenzel Luca Zancato Alessandro Achille Emanuele Rodolà Stefano Soatto Bernhard Schölkopf Francesco Locatello OOD DRL 95 25 0 17 Apr 2023
On the Stepwise Nature of Self-Supervised Learning James B. Simon Maksis Knutins Liu Ziyin Daniel Geisz Abraham J. Fetterman Joshua Albrecht SSL 96 35 0 27 Mar 2023
Identifiability of latent-variable and structural-equation models: from linear to nonlinear Aapo Hyvarinen Ilyes Khemakhem R. Monti CML 113 46 0 06 Feb 2023
Synergies between Disentanglement and Sparsity: Generalization and Identifiability in Multi-Task Learning Sébastien Lachapelle T. Deleu Divyat Mahajan Ioannis Mitliagkas Yoshua Bengio Simon Lacoste-Julien Quentin Bertrand 78 34 0 26 Nov 2022
ImageNet-X: Understanding Model Mistakes with Factor of Variation Annotations Badr Youbi Idrissi Diane Bouchacourt Randall Balestriero Ivan Evtimov C. Hazirbas Nicolas Ballas Pascal Vincent M. Drozdzal David Lopez-Paz Mark Ibrahim VLM ViT 101 46 0 03 Nov 2022
Disentanglement of Correlated Factors via Hausdorff Factorized Support Karsten Roth Mark Ibrahim Zeynep Akata Pascal Vincent Diane Bouchacourt CML OOD CoGe 106 34 0 13 Oct 2022
Relative representations enable zero-shot latent space communication Luca Moschella Valentino Maiorca Marco Fumero Antonio Norelli Francesco Locatello Emanuele Rodolà 118 109 0 30 Sep 2022
A Non-isotropic Probabilistic Take on Proxy-based Deep Metric Learning Michael Kirchhof Karsten Roth Zeynep Akata Enkelejda Kasneci 97 13 0 08 Jul 2022
Guillotine Regularization: Why removing layers is needed to improve generalization in Self-Supervised Learning Florian Bordes Randall Balestriero Q. Garrido Adrien Bardes Pascal Vincent 121 24 0 27 Jun 2022
Contrastive and Non-Contrastive Self-Supervised Learning Recover Global and Local Spectral Embedding Methods Randall Balestriero Yann LeCun SSL 112 135 0 23 May 2022
Towards efficient representation identification in supervised learning Kartik Ahuja Divyat Mahajan Vasilis Syrgkanis Ioannis Mitliagkas CoGe OOD DRL 93 19 0 10 Apr 2022
Beyond Separability: Analyzing the Linear Transferability of Contrastive Representations to Related Subpopulations Jeff Z. HaoChen Colin Wei Ananya Kumar Tengyu Ma 77 39 0 06 Apr 2022
Chaos is a Ladder: A New Theoretical Understanding of Contrastive Learning via Augmentation Overlap Yifei Wang Qi Zhang Yisen Wang Jiansheng Yang Zhouchen Lin 72 102 0 25 Mar 2022
Understanding Dimensional Collapse in Contrastive Self-supervised Learning Li Jing Pascal Vincent Yann LeCun Yuandong Tian SSL 124 359 0 18 Oct 2021
Disentangling Identifiable Features from Noisy Data with Structured Nonlinear ICA Hermanni Hälvä Sylvain Le Corff Luc Lehéricy Jonathan So Yongjie Zhu Elisabeth Gassiat Aapo Hyvarinen CML 69 65 0 17 Jun 2021
Contrastive Learning Inverts the Data Generating Process Roland S. Zimmermann Yash Sharma Steffen Schneider Matthias Bethge Wieland Brendel SSL 376 223 0 17 Feb 2021
Addressing the Topological Defects of Disentanglement via Distributed Operators Diane Bouchacourt Mark Ibrahim Stéphane Deny 38 22 0 10 Feb 2021
Causal Inference from Slowly Varying Nonstationary Processes Kang Du Yu Xiang 121 6 0 23 Dec 2020
Towards Nonlinear Disentanglement in Natural Data with Temporal Sparse Coding David A. Klindt Lukas Schott Yash Sharma Ivan Ustyuzhaninov Wieland Brendel Matthias Bethge Dylan M. Paiton CML 146 134 0 21 Jul 2020
On Linear Identifiability of Learned Representations Geoffrey Roeder Luke Metz Diederik P. Kingma CML 74 85 0 01 Jul 2020
Disentangling by Subspace Diffusion David Pfau I. Higgins Aleksandar Botev S. Racanière DiffM DRL 79 37 0 23 Jun 2020
Independent Innovation Analysis for Nonlinear Vector Autoregressive Process H. Morioka Hermanni Hälvä Aapo Hyvarinen 123 22 0 19 Jun 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 231 2,071 0 16 Apr 2020
A Simple Framework for Contrastive Learning of Visual Representations Ting-Li Chen Simon Kornblith Mohammad Norouzi Geoffrey E. Hinton SSL 431 18,975 0 13 Feb 2020
Weakly-Supervised Disentanglement Without Compromises Francesco Locatello Ben Poole Gunnar Rätsch Bernhard Schölkopf Olivier Bachem Michael Tschannen CoGe OOD DRL 276 321 0 07 Feb 2020
Variational Autoencoders and Nonlinear ICA: A Unifying Framework Ilyes Khemakhem Diederik P. Kingma Ricardo Pio Monti Aapo Hyvarinen OOD 101 599 0 10 Jul 2019
The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA Luigi Gresele Paul Kishan Rubenstein Arash Mehrjou Francesco Locatello Bernhard Schölkopf 57 100 0 16 May 2019
Analytical Methods for Interpretable Ultradense Word Embeddings Philipp Dufter Hinrich Schütze 70 25 0 18 Apr 2019
Analogies Explained: Towards Understanding Word Embeddings Carl Allen Timothy M. Hospedales 94 144 0 28 Jan 2019
Towards a Definition of Disentangled Representations I. Higgins David Amos David Pfau S. Racanière Loic Matthey Danilo Jimenez Rezende Alexander Lerchner OCL DRL 139 480 0 05 Dec 2018
Challenging Common Assumptions in the Unsupervised Learning of Disentangled Representations Francesco Locatello Stefan Bauer Mario Lucic Gunnar Rätsch Sylvain Gelly Bernhard Schölkopf Olivier Bachem OOD 166 1,475 0 29 Nov 2018
ImageNet-trained CNNs are biased towards texture; increasing shape bias improves accuracy and robustness Robert Geirhos Patricia Rubisch Claudio Michaelis Matthias Bethge Felix Wichmann Wieland Brendel 213 2,680 0 29 Nov 2018
Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning Aapo Hyvarinen Hiroaki Sasaki Richard Turner OOD CML 129 331 0 22 May 2018
Unsupervised Feature Learning via Non-Parametric Instance-level Discrimination Zhirong Wu Yuanjun Xiong Stella X. Yu Dahua Lin SSL 196 3,475 0 05 May 2018
Deep Learning is Robust to Massive Label Noise David Rolnick Andreas Veit Serge J. Belongie Nir Shavit NoLa 110 558 0 30 May 2017
Unsupervised Feature Extraction by Time-Contrastive Learning and Nonlinear ICA Aapo Hyvarinen H. Morioka CML OOD AI4TS 79 410 0 20 May 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.5K 195,053 0 10 Dec 2015
Discriminative Unsupervised Feature Learning with Exemplar Convolutional Neural Networks Alexey Dosovitskiy Philipp Fischer Jost Tobias Springenberg Martin Riedmiller Thomas Brox OOD SSL 163 1,026 0 26 Jun 2014
Distributed Representations of Words and Phrases and their Compositionality Tomas Mikolov Ilya Sutskever Kai Chen G. Corrado J. Dean NAI OCL 429 33,605 0 16 Oct 2013