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 58 篇，第 1 / 2 页

1. ICLR 2023Actionable Neural Representations: Grid Cells from Minimal Constraints
2. ICLR 2023Advancing Radiograph Representation Learning with Masked Record Modeling
3. ICLR 2023Anamnesic Neural Differential Equations with Orthogonal Polynomial Projections
4. ICLR 2023Are More Layers Beneficial to Graph Transformers?
5. ICLR 2023Autoencoders as Cross-Modal Teachers: Can Pretrained 2D Image Transformers Help 3D Representation Learning?
6. ICLR 2023Behavior Prior Representation learning for Offline Reinforcement Learning
7. ICLR 2023Bispectral Neural Networks
8. ICLR 2023BrainBERT: Self-supervised representation learning for intracranial recordings
9. ICLR 2023Constructive TT-representation of the tensors given as index interaction functions with applications
10. ICLR 2023Contrastive Learning Can Find An Optimal Basis For Approximately View-Invariant Functions
11. ICLR 2023DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability
12. ICLR 2023Differentiable Mathematical Programming for Object-Centric Representation Learning
13. ICLR 2023Disentanglement of Correlated Factors via Hausdorff Factorized Support
14. ICLR 2023Disentangling Learning Representations with Density Estimation
15. ICLR 2023Edgeformers: Graph-Empowered Transformers for Representation Learning on Textual-Edge Networks
16. ICLR 2023Efficient Conditionally Invariant Representation Learning
17. ICLR 2023Error Sensitivity Modulation based Experience Replay: Mitigating Abrupt Representation Drift in Continual Learning
18. ICLR 2023Evaluating Representations with Readout Model Switching
19. ICLR 2023Finding the Global Semantic Representation in GAN through Fréchet Mean
20. ICLR 2023Gromov-Wasserstein Autoencoders
21. ICLR 2023How robust is unsupervised representation learning to distribution shift?
22. ICLR 2023Hyperbolic Deep Reinforcement Learning
23. ICLR 2023Improving Out-of-distribution Generalization with Indirection Representations
24. ICLR 2023Is a Caption Worth a Thousand Images? A Study on Representation Learning
25. ICLR 2023Language Modelling with Pixels
26. ICLR 2023Latent Variable Representation for Reinforcement Learning
27. ICLR 2023Learning Domain-Agnostic Representation for Disease Diagnosis
28. ICLR 2023Learning Language Representations with Logical Inductive Bias
29. ICLR 2023Learning Structured Representations by Embedding Class Hierarchy
30. ICLR 2023Learning topology-preserving data representations
31. ICLR 2023Logical Entity Representation in Knowledge-Graphs for Differentiable Rule Learning
32. ICLR 2023Logical Message Passing Networks with One-hop Inference on Atomic Formulas
33. ICLR 2023Mitigating Memorization of Noisy Labels via Regularization between Representations
34. ICLR 2023Multivariate Time-series Imputation with Disentangled Temporal Representations
35. ICLR 2023Neural Implicit Shape Editing using Boundary Sensitivity
36. ICLR 2023Neural Radiance Field Codebooks
37. ICLR 2023NORM: Knowledge Distillation via N-to-One Representation Matching
38. ICLR 2023Omnigrok: Grokking Beyond Algorithmic Data
39. ICLR 2023Out-of-distribution Representation Learning for Time Series Classification
40. ICLR 2023Progressively Compressed Auto-Encoder for Self-supervised Representation Learning
41. ICLR 2023Protein Representation Learning by Geometric Structure Pretraining
42. ICLR 2023Proto-Value Networks: Scaling Representation Learning with Auxiliary Tasks
43. ICLR 2023Provably Efficient Lifelong Reinforcement Learning with Linear Representation
44. ICLR 2023Relative representations enable zero-shot latent space communication
45. ICLR 2023Reliability of CKA as a Similarity Measure in Deep Learning
46. ICLR 2023RoPAWS: Robust Semi-supervised Representation Learning from Uncurated Data
47. ICLR 2023Self-Supervised Set Representation Learning for Unsupervised Meta-Learning
48. ICLR 2023SimPer: Simple Self-Supervised Learning of Periodic Targets
49. ICLR 2023Soft Neighbors are Positive Supporters in Contrastive Visual Representation Learning
50. ICLR 2023Spacetime 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。