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← Learning Types
Deep Learning
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Learning Types
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Representation Learning
4,516 papers
Papers per year
2006: 7
2007: 2
2008: 7
2009: 1
2010: 5
2011: 9
2012: 20
2013: 37
2014: 51
2015: 47
2016: 86
2017: 197
2018: 322
2019: 499
2020: 569
2021: 521
2022: 608
2023: 552
2024: 535
2025: 432
2026: 9
Papers
Pairwise Supervised Contrastive Learning of Sentence Representations
EMNLP 2021
Explainable Models with Consistent Interpretations
AAAI 2021
Extreme Low-Light Environment-Driven Image Denoising Over Permanently Shadowed Lunar Regions With a Physical Noise Model
CVPR 2021
Improving Sample Efficiency in Model-Free Reinforcement Learning from Images
AAAI 2021
ValNorm Quantifies Semantics to Reveal Consistent Valence Biases Across Languages and Over Centuries
EMNLP 2021
Instabilities of Offline RL with Pre-Trained Neural Representation
ICML 2021
Contrastive Learning Based Hybrid Networks for Long-Tailed Image Classification
CVPR 2021
Exploring Complementary Strengths of Invariant and Equivariant Representations for Few-Shot Learning
CVPR 2021
A Double Phases Generation Network for Yes or No Question Generation (Student Abstract)
AAAI 2021
Neural Sentence Simplification with Semantic Dependency Information
AAAI 2021
LOHO: Latent Optimization of Hairstyles via Orthogonalization
CVPR 2021
Local Relation Learning for Face Forgery Detection
AAAI 2021
Learning Better Visual Data Similarities via New Grouplet Non-Euclidean Embedding
ICCV 2021
Multi-View Representation Learning with Manifold Smoothness
AAAI 2021
Locate and Label: A Two-stage Identifier for Nested Named Entity Recognition
ACL 2021
Generalized Zero-Shot Learning via Disentangled Representation
AAAI 2021
ReadOnce Transformers: Reusable Representations of Text for Transformers
ACL 2021
Neural Stylistic Response Generation with Disentangled Latent Variables
ACL 2021
Learning with Algorithmic Supervision via Continuous Relaxations
NIPS 2021
Uncertainty-Driven Loss for Single Image Super-Resolution
NIPS 2021
Intriguing Properties of Vision Transformers
NIPS 2021
Learning Graph Cellular Automata
NIPS 2021
Statistically and Computationally Efficient Linear Meta-representation Learning
NIPS 2021
Partition and Code: learning how to compress graphs
NIPS 2021
Recognizing Vector Graphics without Rasterization
NIPS 2021
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