NeurIPS 2024 Past Theory

NeurIPS 2024 Workshop: Self-Supervised Learning - Theory and Practice

NeurIPS 2024 Workshop SSL

Submission deadline
Sep 20, 2024, 11:59 UTC
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Auto-imported from the OpenReview venue record on 2026-06-10 — please verify and enrich (topics are keyword-guessed).

Accepted papers (59)

Fetched from OpenReview (v2) on 2026-06-10.

  1. $\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs

    Vlad Sobal, Mark Ibrahim, Randall Balestriero, Vivien Cabannes, Diane Bouchacourt, Pietro Astolfi, Kyunghyun Cho, Yann LeCun · PDF
  2. A Graph Matching Approach to Balanced Data Sub-Sampling for Self-Supervised Learning

    Hugues Van Assel, Randall Balestriero · PDF
  3. A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning

    Khimya Khetarpal, Zhaohan Daniel Guo, Bernardo Avila Pires, Yunhao Tang, Clare Lyle, Mark Rowland, Nicolas Heess, Diana L Borsa, Arthur Guez, Will Dabney · PDF
  4. Adaptive Neighborhoods in Contrastive Regression Learning for Brain Age Prediction

    Jakob Träuble, Lucy V Hiscox, Curtis Johnson, Carola-Bibiane Schönlieb, Gabriele S Kaminski Schierle, Angelica I Aviles-Rivero · PDF
  5. An Empirical Analysis of Speech Self-Supervised Learning at Multiple Resolutions

    Theo Clark, Benedetta Cevoli, Eloy de Jong, Timofey Abramski, Jamie Dougherty · PDF
  6. Anomaly Detection In The Wild: Can SSL Handle Strong Distribution Imbalances?

    Daniel Otero, Rafael Mateus, Randall Balestriero · PDF
  7. Benchmarking Self-Supervised Learning for Single-Cell Data

    Philip Toma, Olga Ovcharenko, Imant Daunhawer, Julia E Vogt, Florian Barkmann, Valentina Boeva · PDF
  8. Boosting Unsupervised Segmentation Learning

    Alp Eren SARI, Francesco Locatello, Paolo Favaro · PDF
  9. Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing

    Borna Barahimi, Hina Tabassum, Mohammad Omer, Omer Waqar · PDF
  10. Data Augmentation Transformations for Self-Supervised Learning with Ultrasound

    Blake VanBerlo, Alexander Wong, Jesse Hoey, Robert Arntfield · PDF
  11. Decoupling Vertical Federated Learning using Local Self-Supervision

    Avi Amalanshu, Yash Sirvi, David I. Inouye · PDF
  12. DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features

    Attila Juhos, Alice Bizeul, Patrik Reizinger, Randall Balestriero, David Klindt, Mark Ibrahim, Julia E Vogt, Wieland Brendel · PDF
  13. DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks

    Wei Cui, Yi Sui, Jesse C. Cresswell, Keyvan Golestan · PDF
  14. EmbedSimScore: Advancing Protein Similarity Analysis with Structural and Contextual Embeddings

    Gourab Saha, Md Toki Tahmid, Md Shamsuzzoha Bayzid · PDF
  15. Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning

    Etai Littwin, Vimal Thilak, Anand Gopalakrishnan · PDF
  16. Equivariant Representation Learning for Augmentation-based Self-Supervised Learning via Image Reconstruction

    Qin Wang, Kai Krajsek, Hanno Scharr · PDF
  17. Explainable Audio-Visual Representation Learning via Prototypical Contrastive Masked Autoencoder

    Yi Li, Plamen P Angelov · PDF
  18. For Perception Tasks: The Cost of LLM Pretraining by Next-Token Prediction Outweigh its Benefits

    Randall Balestriero, Hai Huang · PDF
  19. Improving OOD Generalization of Pre-trained Encoders via Aligned Embedding-Space Ensembles

    Shuman Peng, Arash Khoeini, Sharan Vaswani, Martin Ester · PDF
  20. In-Context Symmetries: Self-Supervised Learning through Contextual World Models

    Sharut Gupta, Chenyu Wang, Yifei Wang, Tommi Jaakkola, Stefanie Jegelka · PDF
  21. Influence Estimation in Self-Supervised Learning

    Nidhin Harilal, Reza Akbarian Bafghi, Amit Kiran Rege, Maziar Raissi, Claire Monteleoni · PDF
  22. Informed Augmentation Selection Improves Tabular Contrastive Learning

    Arash Khoeini, Shuman Peng, Martin Ester · PDF
  23. Intra-video Positive Pairs in Self-Supervised Learning for Ultrasound

    Blake VanBerlo, Alexander Wong, Jesse Hoey, Robert Arntfield · PDF
  24. Leveraging Audio and Visual Recurrence for Unsupervised Video Highlight Detection

    Zahidul Islam, Sujoy Paul, Mrigank Rochan · PDF
  25. LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation

    Aoqi Wu, weiquan Huang, Yifan Yang, Xufang Luo, Yuqing Yang, Chunyu Wang, Liang Hu, Xiyang Dai, Dongdong Chen, Chong Luo, Lili Qiu · PDF
  26. Masked Self-Supervised Pretraining for Semantic Segmentation of Dental Radiographs

    Tejeswar Pokuri, Laalenthika Konthalapalli, Sarvesh Kumar, Karthik B. V. A. S. · PDF
  27. Maven: A Multimodal Foundation Model for Supernova Science

    Gemma Zhang, Thomas Helfer, Alexander Thomas Gagliano, Siddharth Mishra-Sharma, V Ashley Villar · PDF
  28. MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations

    Benedikt Alkin, Lukas Miklautz, Sepp Hochreiter, Johannes Brandstetter · PDF
  29. NARAIM: Native Aspect Ratio Autoregressive Image Models

    Daniel Gallo Fernández, Robert van der Klis, Răzvan-Andrei Matișan, Janusz Partyka, Samuele Papa, Efstratios Gavves, Phillip Lippe · PDF
  30. Neural Embeddings Rank: Aligning 3D latent dynamics with movements

    Chenggang Chen, Zhiyu Yang · PDF
  31. Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?

    Mark Ibrahim, David Klindt, Randall Balestriero · PDF
  32. On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning

    Bokun Wang, Yunwen Lei, Yiming Ying, Tianbao Yang · PDF
  33. On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models

    Yi Zhang, Difan Zou · PDF
  34. PabLO: Improving Semi-Supervised Learning with Pseudolabeling Optimization

    Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV, Sui Jiet Tay, Ramya Korlakai Vinayak, Frederic Sala · PDF
  35. Pearls from Pebbles: Improved Confidence Functions for Auto-labeling

    Harit Vishwakarma, Yi Chen, Sui Jiet Tay, Satya Sai Srinath Namburi GNVV, Frederic Sala, Ramya Korlakai Vinayak · PDF
  36. PiLaMIM: Toward Richer Visual Representations by Integrating Pixel and Latent Masked Image Modeling

    Junmyeong Lee, Eui Jun Hwang, Sukmin Cho, Jong C. Park · PDF
  37. Representing Positional Information in Generative World Models for Object Manipulation

    Stefano Ferraro, Pietro Mazzaglia, Tim Verbelen, Bart Dhoedt, Sai Rajeswar · PDF
  38. Rethinking Patch Dependence for Masked Autoencoders

    Letian Fu, Long Lian, Renhao Wang, Baifeng Shi, XuDong Wang, Adam Yala, Trevor Darrell, Alexei A Efros, Ken Goldberg · PDF
  39. Robust Self-Supervised Learning for Adversarial Attack Detection

    Yi Li, Plamen P Angelov, Neeraj Suri · PDF
  40. Self Supervised Learning Using Controlled Diffusion Image Augmentation

    Judah A Goldfeder, Patrick Minwan Puma, Gabriel Guo, Gabriel Guerra Trigo, Hod Lipson · PDF
  41. Self-Supervised Bisimulation Action Chunk Representation for Efficient RL

    Lei Shi, Jianye HAO, Hongyao Tang, Zibin Dong, YAN ZHENG · PDF
  42. Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series

    Ching Chang, Chan Chiao-Tung, Wei-Yao Wang, Wen-Chih Peng, Tien-Fu Chen · PDF
  43. Self-Supervised Pretext Tasks for Event Sequence Data from Detecting Misalignment

    Yimu Wang, He Zhao, Ruizhi Deng, Frederick Tung, Greg Mori · PDF
  44. Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps

    Xue Xia, Randall Balestriero, Tao Zhang, Lorenz Hurni · PDF
  45. Seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models

    Hafez Ghaemi, Eilif Benjamin Muller, Shahab Bakhtiari · PDF
  46. SigCLR: Sigmoid Contrastive Learning of Visual Representations

    Ömer Veysel Çağatan · PDF
  47. Squeezing performance from pathology foundation models with chained hyperparameter searches

    Joseph Cappadona, Ken Gary Zeng, Carlos Fernandez-Granda, Jan Witowski, Yann LeCun, Krzysztof J. Geras · PDF
  48. Squeezing Water from a Stone: Improving Pre-Trained Self-Supervised Embeddings Through Effective Entropy Maximization

    Deep Chakraborty, Tim G. J. Rudner, Erik Learned-Miller · PDF
  49. Test-Time Adaptation for Video Highlight Detection

    Zahidul Islam, Sujoy Paul, Mrigank Rochan · PDF
  50. The Birth of Self Supervised Learning: A Supervised Theory

    Randall Balestriero, Yann LeCun · PDF
  51. Time-varying Representations of Longitudinal Biosignals using Self-supervised Learning

    Sam Jean Perochon, Salar Abbaspourazad, Joseph Futoma, Andrew Miller, Guillermo Sapiro · PDF
  52. TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection

    Boje Deforce, Meng-Chieh Lee, Bart Baesens, Estefanía Serral Asensio, Jaemin Yoo, Leman Akoglu · PDF
  53. Two Is Better Than One: Aligned Clusters Improve Anomaly Detection

    Alain Ryser, Thomas M. Sutter, Alexander Marx, Julia E Vogt · PDF
  54. Uncovering RL Integration in SSL Loss: Objective-Specific Implications for Data-Efficient RL

    Ömer Veysel Çağatan, Baris Akgun · PDF
  55. Uncovering the Risk of Model Collapsing in Self-Supervised Continual Test-time Adaptation

    Trung-Hieu Hoang, MinhDuc Vo, Minh N. Do · PDF
  56. Unfolding Videos Dynamics via Taylor Expansion

    Siyi Chen, Minkyu Choi, Zesen Zhao, Kuan Han, Qing Qu, Zhongming Liu · PDF
  57. Unsupervised Event Outlier Detection in Continuous Time

    Somjit Nath, Kry Yik-Chau Lui, Siqi Liu · PDF
  58. Variational Graph Contrastive Learning

    Shifeng Xie, Jhony H. Giraldo · PDF
  59. When Do We Not Need Larger Vision Models?

    Baifeng Shi, Ziyang Wu, Maolin Mao, Xin Wang, Trevor Darrell · PDF