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← Learning Types
Machine Learning
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Learning Types
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Self-Supervised Learning
8,255 papers
Papers per year
2006: 8
2007: 7
2008: 7
2009: 9
2010: 12
2011: 7
2012: 13
2013: 11
2014: 12
2015: 17
2016: 35
2017: 97
2018: 191
2019: 441
2020: 663
2021: 1166
2022: 1170
2023: 1544
2024: 1323
2025: 1205
2026: 317
Papers
Global Lyapunov functions: a long-standing open problem in mathematics, with symbolic transformers
NIPS 2024
Accelerating Augmentation Invariance Pretraining
NIPS 2024
Diffusion-Reward Adversarial Imitation Learning
NIPS 2024
Preventing Dimensional Collapse in Self-Supervised Learning via Orthogonality Regularization
NIPS 2024
Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT
NIPS 2024
Identify Then Recommend: Towards Unsupervised Group Recommendation
NIPS 2024
A distributional simplicity bias in the learning dynamics of transformers
NIPS 2024
Latent Intrinsics Emerge from Training to Relight
NIPS 2024
Few-Shot Task Learning through Inverse Generative Modeling
NIPS 2024
Uncovering the Redundancy in Graph Self-supervised Learning Models
NIPS 2024
Hierarchy-Agnostic Unsupervised Segmentation: Parsing Semantic Image Structure
NIPS 2024
OwMatch: Conditional Self-Labeling with Consistency for Open-World Semi-Supervised Learning
NIPS 2024
Self-Consuming Generative Models with Curated Data Provably Optimize Human Preferences
NIPS 2024
Pretraining Codomain Attention Neural Operators for Solving Multiphysics PDEs
NIPS 2024
In-Context Symmetries: Self-Supervised Learning through Contextual World Models
NIPS 2024
M3LEO: A Multi-Modal, Multi-Label Earth Observation Dataset Integrating Interferometric SAR and Multispectral Data
NIPS 2024
Disentangled Representation Learning in Non-Markovian Causal Systems
NIPS 2024
Boosting Semi-Supervised Scene Text Recognition via Viewing and Summarizing
NIPS 2024
Self-Labeling the Job Shop Scheduling Problem
NIPS 2024
CycleNet: Enhancing Time Series Forecasting through Modeling Periodic Patterns
NIPS 2024
Online Feature Updates Improve Online (Generalized) Label Shift Adaptation
NIPS 2024
Learning to Edit Visual Programs with Self-Supervision
NIPS 2024
Con4m: Context-aware Consistency Learning Framework for Segmented Time Series Classification
NIPS 2024
Compositional Generalization Across Distributional Shifts with Sparse Tree Operations
NIPS 2024
PowerPM: Foundation Model for Power Systems
NIPS 2024
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