深度学习 · representation learning论文趋势 2023–2026

主要结论

• 深度学习 · representation learning论文从 2023 年的 259 篇降到 2026 年的 214 篇，热度在回落。
• NeurIPS 是发深度学习 · representation learning论文最多的会议，2023–2026 年共 279 篇，占四个会议总量的 35%。
• 交叉方向里涨得最快的是多模态大模型：同时属于两个主题的论文从 2023 年的 11 篇增至 2026 年的 28 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 7；同组增长最快的扩散模型是 4.1 倍，深度学习 · representation learning是 0.8 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• NeurIPS 2026Active Learning as Nullspace Regulation: A Spectral Representation Perspective
• ICML 2026Addressing Instrument-Outcome Confounding in Mendelian Randomization through Representation Learning
• ICLR 2026Boosting Open Set Recognition Performance through Modulated Representation Learning
• CVPR 2026CanonCGT Reference-Based Color Grading via Canonical Pivot Representation
• NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
• ICML 2025Banyan: Improved Representation Learning with Explicit Structure
• ICLR 2025Edge-aware Image Smoothing with Relative Wavelet Domain Representation
• CVPR 20253D-SLNR: A Super Lightweight Neural Representation for Large-scale 3D Mapping
• NeurIPS 2024GV-Rep: A Large-Scale Dataset for Genetic Variant Representation Learning
• ICML 2024Data-free Neural Representation Compression with Riemannian Neural Dynamics
• ICLR 2024$\texttt{NAISR}$: A 3D Neural Additive Model for Interpretable Shape Representation
• CVPR 2024Disentangled Prompt Representation for Domain Generalization
• NeurIPS 2023[Re] CrossWalk: Fairness-enhanced Node Representation Learning
• ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
• ICLR 2023Bispectral Neural Networks
• CVPR 2023AnyFlow: Arbitrary Scale Optical Flow With Implicit Neural Representation
• NeurIPS 2026Approximation in Contrastive Representation Learning
• ICML 2026Amortized Maximum Inner Product Search with Learned Support Functions
• ICLR 2026Decoupling Dynamical Richness from Representation Learning: Towards Practical Measurement
• CVPR 2026Enhancing Visual Representation with Textual Semantics Textual Semantics-Powered Prototypes for

全部深度学习 · representation learning论文

共 31 篇，第 1 / 1 页

1. ICML 2023A General Representation Learning Framework with Generalization Performance Guarantees
2. ICML 2023A theory of representation learning gives a deep generalisation of kernel methods
3. ICML 2023Adversarial Collaborative Learning on Non-IID Features
4. ICML 2023Contrast with Reconstruct: Contrastive 3D Representation Learning Guided by Generative Pretraining
5. ICML 2023Deep Graph Representation Learning and Optimization for Influence Maximization
6. ICML 2023Defects of Convolutional Decoder Networks in Frequency Representation
7. ICML 2023Diffusion Based Representation Learning
8. ICML 2023Disentangled Multiplex Graph Representation Learning
9. ICML 2023Dynamics-inspired Neuromorphic Visual Representation Learning
10. ICML 2023Entropy-driven Unsupervised Keypoint Representation Learning in Videos
11. ICML 2023FARE: Provably Fair Representation Learning with Practical Certificates
12. ICML 2023Feature Directions Matter: Long-Tailed Learning via Rotated Balanced Representation
13. ICML 2023FedCR: Personalized Federated Learning Based on Across-Client Common Representation with Conditional Mutual Information Regularization
14. ICML 2023Generalization Analysis for Contrastive Representation Learning
15. ICML 2023Hyperbolic Representation Learning: Revisiting and Advancing
16. ICML 2023InfoDiffusion: Representation Learning Using Information Maximizing Diffusion Models
17. ICML 2023Internet Explorer: Targeted Representation Learning on the Open Web
18. ICML 2023Interventional Causal Representation Learning
19. ICML 2023Learning Affinity with Hyperbolic Representation for Spatial Propagation
20. ICML 2023Multi-task Representation Learning for Pure Exploration in Linear Bandits
21. ICML 2023On the Importance of Feature Decorrelation for Unsupervised Representation Learning in Reinforcement Learning
22. ICML 2023Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
23. ICML 2023Provably Efficient Representation Learning with Tractable Planning in Low-Rank POMDP
24. ICML 2023Representation-Driven Reinforcement Learning
25. ICML 2023Ske2Grid: Skeleton-to-Grid Representation Learning for Action Recognition
26. ICML 2023Stochastic Gradient Descent-Induced Drift of Representation in a Two-Layer Neural Network
27. ICML 2023The Numerical Stability of Hyperbolic Representation Learning
28. ICML 2023Tied-Augment: Controlling Representation Similarity Improves Data Augmentation
29. ICML 2023Towards a better understanding of representation dynamics under TD-learning
30. ICML 2023Towards Better Graph Representation Learning with Parameterized Decomposition & Filtering
31. ICML 2023Weakly Supervised Disentangled Generative Causal Representation Learning

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · representation learning论文？

共 802 篇，按年份分别是 2023 年 259 篇、2024 年 177 篇、2025 年 152 篇、2026 年 214 篇。

NeurIPS 2026 有多少篇深度学习 · representation learning论文？

NeurIPS 2026 有 59 篇深度学习 · representation learning论文，上一届是 54 篇。

ICLR 2026 有多少篇深度学习 · representation learning论文？

ICLR 2026 有 39 篇深度学习 · representation learning论文，上一届是 37 篇。

ICML 2026 有多少篇深度学习 · representation learning论文？

ICML 2026 有 74 篇深度学习 · representation learning论文，上一届是 35 篇。

CVPR 2026 有多少篇深度学习 · representation learning论文？

CVPR 2026 有 42 篇深度学习 · representation learning论文，上一届是 26 篇。

哪个会议的深度学习 · representation learning论文最多？

NeurIPS，2023–2026 年共 279 篇。