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Methodology
← Learning Types
Deep Learning
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Learning Types
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Representation Learning
4516 directly classified 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
Dual Memory Aggregation Network for Event-Based Object Detection with Learnable Representation
AAAI 2023
Cross-View Geo-Localization via Learning Disentangled Geometric Layout Correspondence
AAAI 2023
Curriculum Multi-Negative Augmentation for Debiased Video Grounding
AAAI 2023
Learning Representations without Compositional Assumptions
ICML 2023
MRCN: A Novel Modality Restitution and Compensation Network for Visible-Infrared Person Re-identification
AAAI 2023
Deep Graph Representation Learning and Optimization for Influence Maximization
ICML 2023
Learning Fractals by Gradient Descent
AAAI 2023
Hyperbolic Diffusion Embedding and Distance for Hierarchical Representation Learning
ICML 2023
Conditional Graph Information Bottleneck for Molecular Relational Learning
ICML 2023
Rotation and Translation Invariant Representation Learning with Implicit Neural Representations
ICML 2023
Learning Attribute and Class-Specific Representation Duet for Fine-Grained Fashion Analysis
CVPR 2023
RePreM: Representation Pre-training with Masked Model for Reinforcement Learning
AAAI 2023
GOAT: A Global Transformer on Large-scale Graphs
ICML 2023
IncDSI: Incrementally Updatable Document Retrieval
ICML 2023
Stable and Consistent Prediction of 3D Characteristic Orientation via Invariant Residual Learning
ICML 2023
Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
ICML 2023
Homomorphism AutoEncoder -- Learning Group Structured Representations from Observed Transitions
ICML 2023
Neural Wave Machines: Learning Spatiotemporally Structured Representations with Locally Coupled Oscillatory Recurrent Neural Networks
ICML 2023
Node Embedding from Neural Hamiltonian Orbits in Graph Neural Networks
ICML 2023
Fantastic Breaks: A Dataset of Paired 3D Scans of Real-World Broken Objects and Their Complete Counterparts
CVPR 2023
Leveraging Proxy of Training Data for Test-Time Adaptation
ICML 2023
Neural Texture Synthesis With Guided Correspondence
CVPR 2023
Robust Multiview Point Cloud Registration With Reliable Pose Graph Initialization and History Reweighting
CVPR 2023
Understanding Representation Learnability of Nonlinear Self-Supervised Learning
AAAI 2023
Equivariance with Learned Canonicalization Functions
ICML 2023
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