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 imported from OpenReview — check the website for extensions
- Submission portal
- OpenReview
- Notes
- 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.
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$\mathbb{X}$-Sample Contrastive Loss: Improving Contrastive Learning with Sample Similarity Graphs
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A Graph Matching Approach to Balanced Data Sub-Sampling for Self-Supervised Learning
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A Unifying Framework for Action-Conditional Self-Predictive Reinforcement Learning
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Adaptive Neighborhoods in Contrastive Regression Learning for Brain Age Prediction
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An Empirical Analysis of Speech Self-Supervised Learning at Multiple Resolutions
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Anomaly Detection In The Wild: Can SSL Handle Strong Distribution Imbalances?
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Benchmarking Self-Supervised Learning for Single-Cell Data
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Boosting Unsupervised Segmentation Learning
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Context-Aware Predictive Coding: A Representation Learning Framework for WiFi Sensing
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Data Augmentation Transformations for Self-Supervised Learning with Ultrasound
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Decoupling Vertical Federated Learning using Local Self-Supervision
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DIETing: Self-Supervised Learning with Instance Discrimination Learns Identifiable Features
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DRESS: Disentangled Representation-based Self-Supervised Meta-Learning for Diverse Tasks
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EmbedSimScore: Advancing Protein Similarity Analysis with Structural and Contextual Embeddings
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Enhancing JEPAs with Spatial Conditioning: Robust and Efficient Representation Learning
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Equivariant Representation Learning for Augmentation-based Self-Supervised Learning via Image Reconstruction
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Explainable Audio-Visual Representation Learning via Prototypical Contrastive Masked Autoencoder
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For Perception Tasks: The Cost of LLM Pretraining by Next-Token Prediction Outweigh its Benefits
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Improving OOD Generalization of Pre-trained Encoders via Aligned Embedding-Space Ensembles
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In-Context Symmetries: Self-Supervised Learning through Contextual World Models
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Influence Estimation in Self-Supervised Learning
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Informed Augmentation Selection Improves Tabular Contrastive Learning
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Intra-video Positive Pairs in Self-Supervised Learning for Ultrasound
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Leveraging Audio and Visual Recurrence for Unsupervised Video Highlight Detection
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LLM2CLIP: Powerful Language Model Unlock Richer Visual Representation
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Masked Self-Supervised Pretraining for Semantic Segmentation of Dental Radiographs
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Maven: A Multimodal Foundation Model for Supernova Science
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MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Representations
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NARAIM: Native Aspect Ratio Autoregressive Image Models
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Neural Embeddings Rank: Aligning 3D latent dynamics with movements
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Occam's Razor for Self Supervised Learning: What is Sufficient to Learn Good Representations?
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On Discriminative Probabilistic Modeling for Self-Supervised Representation Learning
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On the Collapse Errors Induced by the Deterministic Sampler for Diffusion Models
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PabLO: Improving Semi-Supervised Learning with Pseudolabeling Optimization
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Pearls from Pebbles: Improved Confidence Functions for Auto-labeling
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PiLaMIM: Toward Richer Visual Representations by Integrating Pixel and Latent Masked Image Modeling
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Representing Positional Information in Generative World Models for Object Manipulation
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Rethinking Patch Dependence for Masked Autoencoders
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Robust Self-Supervised Learning for Adversarial Attack Detection
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Self Supervised Learning Using Controlled Diffusion Image Augmentation
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Self-Supervised Bisimulation Action Chunk Representation for Efficient RL
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Self-Supervised Learning of Disentangled Representations for Multivariate Time-Series
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Self-Supervised Pretext Tasks for Event Sequence Data from Detecting Misalignment
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Self-supervised Video Instance Segmentation Can Boost Geographic Entity Alignment in Historical Maps
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Seq-JEPA: Autoregressive Predictive Learning of Invariant-Equivariant World Models
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SigCLR: Sigmoid Contrastive Learning of Visual Representations
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Squeezing performance from pathology foundation models with chained hyperparameter searches
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Squeezing Water from a Stone: Improving Pre-Trained Self-Supervised Embeddings Through Effective Entropy Maximization
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Test-Time Adaptation for Video Highlight Detection
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The Birth of Self Supervised Learning: A Supervised Theory
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Time-varying Representations of Longitudinal Biosignals using Self-supervised Learning
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TSA on AutoPilot: Self-tuning Self-supervised Time Series Anomaly Detection
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Two Is Better Than One: Aligned Clusters Improve Anomaly Detection
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Uncovering RL Integration in SSL Loss: Objective-Specific Implications for Data-Efficient RL
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Uncovering the Risk of Model Collapsing in Self-Supervised Continual Test-time Adaptation
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Unfolding Videos Dynamics via Taylor Expansion
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Unsupervised Event Outlier Detection in Continuous Time
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Variational Graph Contrastive Learning
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When Do We Not Need Larger Vision Models?