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

ICML/NeurIPS 深度学习方向:representation_learning

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 802 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

深度学习 · representation learning论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023112583158259
202454384243177
202554373526152
202659397442214

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

全部深度学习 · representation learning论文

共 802 篇,第 16 / 17 页

  1. NeurIPS 2023Minimum Description Length and Generalization Guarantees for Representation Learning
  2. NeurIPS 2023Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
  3. NeurIPS 2023Multimodal Deep Learning Model Unveils Behavioral Dynamics of V1 Activity in Freely Moving Mice
  4. NeurIPS 2023MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data
  5. NeurIPS 2023NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
  6. NeurIPS 2023NCDL: A Framework for Deep Learning on non-Cartesian Lattices
  7. NeurIPS 2023Near-optimal learning with average Hölder smoothness
  8. NeurIPS 2023No Representation Rules Them All in Category Discovery
  9. NeurIPS 2023Nonparametric Identifiability of Causal Representations from Unknown Interventions
  10. NeurIPS 2023Object-centric Learning with Cyclic Walks between Parts and Whole
  11. NeurIPS 2023Optimistic Rates for Multi-Task Representation Learning
  12. NeurIPS 2023PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation
  13. NeurIPS 2023PlanE: Representation Learning over Planar Graphs
  14. NeurIPS 2023Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
  15. NeurIPS 2023Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks
  16. NeurIPS 2023Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion
  17. NeurIPS 2023PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
  18. NeurIPS 2023PyNeRF: Pyramidal Neural Radiance Fields
  19. NeurIPS 2023Rank-N-Contrast: Learning Continuous Representations for Regression
  20. NeurIPS 2023Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
  21. NeurIPS 2023Reining Generalization in Offline Reinforcement Learning via Representation Distinction
  22. NeurIPS 2023RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability
  23. NeurIPS 2023Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
  24. NeurIPS 2023Representation Learning via Consistent Assignment of Views over Random Partitions
  25. NeurIPS 2023Reproducibility study of the Fairness-enhanced Node Representation Learning
  26. NeurIPS 2023RevColV2: Exploring Disentangled Representations in Masked Image Modeling
  27. NeurIPS 2023Reverse Engineering Self-Supervised Learning
  28. NeurIPS 2023RGMIL: Guide Your Multiple-Instance Learning Model with Regressor
  29. NeurIPS 2023Robust Concept Erasure via Kernelized Rate-Distortion Maximization
  30. NeurIPS 2023Rotating Features for Object Discovery
  31. NeurIPS 2023SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning
  32. NeurIPS 2023Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
  33. NeurIPS 2023Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation
  34. NeurIPS 2023SLIBO-Net: Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization
  35. NeurIPS 2023Slot-guided Volumetric Object Radiance Fields
  36. NeurIPS 2023StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners
  37. NeurIPS 2023State Sequences Prediction via Fourier Transform for Representation Learning
  38. NeurIPS 2023STREAMER: Streaming Representation Learning and Event Segmentation in a Hierarchical Manner
  39. NeurIPS 2023Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
  40. NeurIPS 2023Temporally Disentangled Representation Learning under Unknown Nonstationarity
  41. NeurIPS 2023The Tunnel Effect: Building Data Representations in Deep Neural Networks
  42. NeurIPS 2023TopoSRL: Topology preserving self-supervised Simplicial Representation Learning
  43. NeurIPS 2023Towards a Unified Framework of Contrastive Learning for Disentangled Representations
  44. NeurIPS 2023Towards In-context Scene Understanding
  45. NeurIPS 2023Towards the Difficulty for a Deep Neural Network to Learn Concepts of Different Complexities
  46. NeurIPS 2023Tree Variational Autoencoders
  47. NeurIPS 2023Uncovering Meanings of Embeddings via Partial Orthogonality
  48. NeurIPS 2023Uncovering Neural Scaling Laws in Molecular Representation Learning
  49. NeurIPS 2023Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera
  50. NeurIPS 2023URL: A Representation Learning Benchmark for Transferable Uncertainty Estimates

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查深度学习 · representation learning在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "dl-representation-learning"}

两分钟接入 Paperlist MCP(Claude Code、Cursor、Codex、ChatGPT)

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。

「深度学习」下的其他主题