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Methodology
← Learning Types
Machine Learning
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Learning Types
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Self-Supervised Learning
8255 directly classified 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
Learning Representations by Maximizing Mutual Information Across Views
NIPS 2019
A Similarity-preserving Network Trained on Transformed Images Recapitulates Salient Features of the Fly Motion Detection Circuit
NIPS 2019
Emergence of Object Segmentation in Perturbed Generative Models
NIPS 2019
Using Self-Supervised Learning Can Improve Model Robustness and Uncertainty
NIPS 2019
Self-Supervised Deep Learning on Point Clouds by Reconstructing Space
NIPS 2019
Data Parameters: A New Family of Parameters for Learning a Differentiable Curriculum
NIPS 2019
Characterizing Bias in Classifiers using Generative Models
NIPS 2019
Information Competing Process for Learning Diversified Representations
NIPS 2019
Meta-Reinforced Synthetic Data for One-Shot Fine-Grained Visual Recognition
NIPS 2019
Joint-task Self-supervised Learning for Temporal Correspondence
NIPS 2019
Wasserstein Dependency Measure for Representation Learning
NIPS 2019
Unsupervised Curricula for Visual Meta-Reinforcement Learning
NIPS 2019
Learning Latent Process from High-Dimensional Event Sequences via Efficient Sampling
NIPS 2019
Curriculum-guided Hindsight Experience Replay
NIPS 2019
Regularizing Trajectory Optimization with Denoising Autoencoders
NIPS 2019
Discovery of Useful Questions as Auxiliary Tasks
NIPS 2019
The Cells Out of Sample (COOS) dataset and benchmarks for measuring out-of-sample generalization of image classifiers
NIPS 2019
Re-examination of the Role of Latent Variables in Sequence Modeling
NIPS 2019
Learning to Learn By Self-Critique
NIPS 2019
Learning about an exponential amount of conditional distributions
NIPS 2019
Zero-shot Learning via Simultaneous Generating and Learning
NIPS 2019
End-To-End Interpretable Neural Motion Planner
CVPR 2019
Occlusion-Net: 2D/3D Occluded Keypoint Localization Using Graph Networks
CVPR 2019
Learning Independent Object Motion From Unlabelled Stereoscopic Videos
CVPR 2019
Self-Supervised Representation Learning by Rotation Feature Decoupling
CVPR 2019
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