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 177 篇，第 2 / 4 页

51. ICLR 2024Decongestion by Representation: Learning to Improve Economic Welfare in Marketplaces
52. ICLR 2024Evaluating Representation Learning on the Protein Structure Universe
53. ICLR 2024Fast Updating Truncated SVD for Representation Learning with Sparse Matrices
54. ICLR 2024Feature Collapse
55. ICLR 2024Guiding Masked Representation Learning to Capture Spatio-Temporal Relationship of Electrocardiogram
56. ICLR 2024Implicit Gaussian process representation of vector fields over arbitrary latent manifolds
57. ICLR 2024Implicit Neural Representation Inference for Low-Dimensional Bayesian Deep Learning
58. ICLR 2024Investigating the Benefits of Projection Head for Representation Learning
59. ICLR 2024Learning Implicit Representation for Reconstructing Articulated Objects
60. ICLR 2024Let Models Speak Ciphers: Multiagent Debate through Embeddings
61. ICLR 2024MAP IT to Visualize Representations
62. ICLR 2024Modelling complex vector drawings with stroke-clouds
63. ICLR 2024NfgTransformer: Equivariant Representation Learning for Normal-form Games
64. ICLR 2024On the Role of Discrete Tokenization in Visual Representation Learning
65. ICLR 2024Polynomial Width is Sufficient for Set Representation with High-dimensional Features
66. ICLR 2024Predictive auxiliary objectives in deep RL mimic learning in the brain
67. ICLR 2024Probabilistic Self-supervised Representation Learning via Scoring Rules Minimization
68. ICLR 2024Proper Laplacian Representation Learning
69. ICLR 2024Protein-ligand binding representation learning from fine-grained interactions
70. ICLR 2024PTaRL: Prototype-based Tabular Representation Learning via Space Calibration
71. ICLR 2024Self-supervised Representation Learning from Random Data Projectors
72. ICLR 2024Separating common from salient patterns with Contrastive Representation Learning
73. ICLR 2024SetCSE: Set Operations using Contrastive Learning of Sentence Embeddings
74. ICLR 2024Simplicial Representation Learning with Neural $k$-Forms
75. ICLR 2024SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
76. ICLR 2024State Representation Learning Using an Unbalanced Atlas
77. ICLR 2024Structuring Representation Geometry with Rotationally Equivariant Contrastive Learning
78. ICLR 2024Symbol as Points: Panoptic Symbol Spotting via Point-based Representation
79. ICLR 2024T-Rep: Representation Learning for Time Series using Time-Embeddings
80. ICLR 2024Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning
81. ICLR 2024Towards Principled Representation Learning from Videos for Reinforcement Learning
82. ICML 2024A Distributional Analogue to the Successor Representation
83. ICML 2024A Sparsity Principle for Partially Observable Causal Representation Learning
84. ICML 2024Autoencoding Conditional Neural Processes for Representation Learning
85. ICML 2024Causal Representation Learning from Multiple Distributions: A General Setting
86. ICML 2024Causal Representation Learning Made Identifiable by Grouping of Observational Variables
87. ICML 2024Contrastive Representation for Data Filtering in Cross-Domain Offline Reinforcement Learning
88. ICML 2024Data-free Neural Representation Compression with Riemannian Neural Dynamics
89. ICML 2024Deep Regression Representation Learning with Topology
90. ICML 2024Denoising Autoregressive Representation Learning
91. ICML 2024Differentiable Mapper for Topological Optimization of Data Representation
92. ICML 2024Differentially Private Representation Learning via Image Captioning
93. ICML 2024Enhancing Size Generalization in Graph Neural Networks through Disentangled Representation Learning
94. ICML 2024Evolution-Inspired Loss Functions for Protein Representation Learning
95. ICML 2024Feasibility Consistent Representation Learning for Safe Reinforcement Learning
96. ICML 2024Federated Representation Learning in the Under-Parameterized Regime
97. ICML 2024Few-Shot Unsupervised Implicit Neural Shape Representation Learning with Spatial Adversaries
98. ICML 2024Finding NEM-U: Explaining unsupervised representation learning through neural network generated explanation masks
99. ICML 2024GeoMFormer: A General Architecture for Geometric Molecular Representation Learning
100. ICML 2024Graph2Tac: Online Representation Learning of Formal Math Concepts

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。