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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
Self-Supervised Learning with Kernel Dependence Maximization
NIPS 2021
Motif-based Graph Self-Supervised Learning for Molecular Property Prediction
NIPS 2021
Adversarial Graph Augmentation to Improve Graph Contrastive Learning
NIPS 2021
DualNet: Continual Learning, Fast and Slow
NIPS 2021
Revisiting Contrastive Methods for Unsupervised Learning of Visual Representations
NIPS 2021
Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style
NIPS 2021
Self-Supervised Representation Learning on Neural Network Weights for Model Characteristic Prediction
NIPS 2021
Large-Scale Unsupervised Object Discovery
NIPS 2021
Dynamic Bottleneck for Robust Self-Supervised Exploration
NIPS 2021
Improving Transferability of Representations via Augmentation-Aware Self-Supervision
NIPS 2021
Structured Denoising Diffusion Models in Discrete State-Spaces
NIPS 2021
Self-Supervised Learning Disentangled Group Representation as Feature
NIPS 2021
Supervising the Transfer of Reasoning Patterns in VQA
NIPS 2021
All Tokens Matter: Token Labeling for Training Better Vision Transformers
NIPS 2021
SubTab: Subsetting Features of Tabular Data for Self-Supervised Representation Learning
NIPS 2021
ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction
NIPS 2021
REMIPS: Physically Consistent 3D Reconstruction of Multiple Interacting People under Weak Supervision
NIPS 2021
Towards Open-World Feature Extrapolation: An Inductive Graph Learning Approach
NIPS 2021
Compressive Visual Representations
NIPS 2021
Generic Neural Architecture Search via Regression
NIPS 2021
Interesting Object, Curious Agent: Learning Task-Agnostic Exploration
NIPS 2021
Techniques for Symbol Grounding with SATNet
NIPS 2021
Supercharging Imbalanced Data Learning With Energy-based Contrastive Representation Transfer
NIPS 2021
PARP: Prune, Adjust and Re-Prune for Self-Supervised Speech Recognition
NIPS 2021
When does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?
NIPS 2021
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