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 112 篇，第 2 / 3 页

51. NeurIPS 2023Invariant Learning via Probability of Sufficient and Necessary Causes
52. NeurIPS 2023Isometric Quotient Variational Auto-Encoders for Structure-Preserving Representation Learning
53. NeurIPS 2023Learning Interpretable Low-dimensional Representation via Physical Symmetry
54. NeurIPS 2023Learning Invariant Molecular Representation in Latent Discrete Space
55. NeurIPS 2023Learning Time-Invariant Representations for Individual Neurons from Population Dynamics
56. NeurIPS 2023Locality-Aware Generalizable Implicit Neural Representation
57. NeurIPS 2023Lovász Principle for Unsupervised Graph Representation Learning
58. NeurIPS 2023MARBLE: Music Audio Representation Benchmark for Universal Evaluation
59. NeurIPS 2023MAViL: Masked Audio-Video Learners
60. NeurIPS 2023May the Force be with You: Unified Force-Centric Pre-Training for 3D Molecular Conformations
61. NeurIPS 2023Minimum Description Length and Generalization Guarantees for Representation Learning
62. NeurIPS 2023Multi-task Representation Learning for Pure Exploration in Bilinear Bandits
63. NeurIPS 2023Multimodal Deep Learning Model Unveils Behavioral Dynamics of V1 Activity in Freely Moving Mice
64. NeurIPS 2023MuSe-GNN: Learning Unified Gene Representation From Multimodal Biological Graph Data
65. NeurIPS 2023NAR-Former V2: Rethinking Transformer for Universal Neural Network Representation Learning
66. NeurIPS 2023NCDL: A Framework for Deep Learning on non-Cartesian Lattices
67. NeurIPS 2023Near-optimal learning with average Hölder smoothness
68. NeurIPS 2023No Representation Rules Them All in Category Discovery
69. NeurIPS 2023Nonparametric Identifiability of Causal Representations from Unknown Interventions
70. NeurIPS 2023Object-centric Learning with Cyclic Walks between Parts and Whole
71. NeurIPS 2023Optimistic Rates for Multi-Task Representation Learning
72. NeurIPS 2023PDF: Point Diffusion Implicit Function for Large-scale Scene Neural Representation
73. NeurIPS 2023PlanE: Representation Learning over Planar Graphs
74. NeurIPS 2023Primal-Attention: Self-attention through Asymmetric Kernel SVD in Primal Representation
75. NeurIPS 2023Provable Guarantees for Nonlinear Feature Learning in Three-Layer Neural Networks
76. NeurIPS 2023Public Opinion Field Effect Fusion in Representation Learning for Trending Topics Diffusion
77. NeurIPS 2023PUG: Photorealistic and Semantically Controllable Synthetic Data for Representation Learning
78. NeurIPS 2023PyNeRF: Pyramidal Neural Radiance Fields
79. NeurIPS 2023Rank-N-Contrast: Learning Continuous Representations for Regression
80. NeurIPS 2023Reading Relevant Feature from Global Representation Memory for Visual Object Tracking
81. NeurIPS 2023Reining Generalization in Offline Reinforcement Learning via Representation Distinction
82. NeurIPS 2023RePo: Resilient Model-Based Reinforcement Learning by Regularizing Posterior Predictability
83. NeurIPS 2023Representation Equivalent Neural Operators: a Framework for Alias-free Operator Learning
84. NeurIPS 2023Representation Learning via Consistent Assignment of Views over Random Partitions
85. NeurIPS 2023Reproducibility study of the Fairness-enhanced Node Representation Learning
86. NeurIPS 2023RevColV2: Exploring Disentangled Representations in Masked Image Modeling
87. NeurIPS 2023Reverse Engineering Self-Supervised Learning
88. NeurIPS 2023RGMIL: Guide Your Multiple-Instance Learning Model with Regressor
89. NeurIPS 2023Robust Concept Erasure via Kernelized Rate-Distortion Maximization
90. NeurIPS 2023Rotating Features for Object Discovery
91. NeurIPS 2023SaVeNet: A Scalable Vector Network for Enhanced Molecular Representation Learning
92. NeurIPS 2023Self-Weighted Contrastive Learning among Multiple Views for Mitigating Representation Degeneration
93. NeurIPS 2023Semi-Supervised Contrastive Learning for Deep Regression with Ordinal Rankings from Spectral Seriation
94. NeurIPS 2023SLIBO-Net: Floorplan Reconstruction via Slicing Box Representation with Local Geometry Regularization
95. NeurIPS 2023Slot-guided Volumetric Object Radiance Fields
96. NeurIPS 2023StableRep: Synthetic Images from Text-to-Image Models Make Strong Visual Representation Learners
97. NeurIPS 2023State Sequences Prediction via Fourier Transform for Representation Learning
98. NeurIPS 2023STREAMER: Streaming Representation Learning and Event Segmentation in a Hierarchical Manner
99. NeurIPS 2023Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
100. NeurIPS 2023Temporally Disentangled Representation Learning under Unknown Nonstationarity

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。