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
- 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。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 112 | 58 | 31 | 58 | 259 |
| 2024 | 54 | 38 | 42 | 43 | 177 |
| 2025 | 54 | 37 | 35 | 26 | 152 |
| 2026 | 59 | 39 | 74 | 42 | 214 |
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 802 篇，第 7 / 17 页
- ICML 2025Random Feature Representation Boosting
- ICML 2025Reconstructing Cell Lineage Trees from Phenotypic Features with Metric Learning
- ICML 2025Representation Preserving Multiclass Agnostic to Realizable Reduction
- ICML 2025sciLaMA: A Single-Cell Representation Learning Framework to Leverage Prior Knowledge from Large Language Models
- ICML 2025Score-based Pullback Riemannian Geometry: Extracting the Data Manifold Geometry using Anisotropic Flows
- ICML 2025Sliding Puzzles Gym: A Scalable Benchmark for State Representation in Visual Reinforcement Learning
- ICML 2025Stabilizing Sample Similarity in Representation via Mitigating Random Consistency
- ICML 2025Stable Fair Graph Representation Learning with Lipschitz Constraint
- ICML 2025Structure Is All You Need: Structural Representation Learning on Hyper-Relational Knowledge Graphs
- ICML 2025The Complexity of Learning Sparse Superposed Features with Feedback
- ICML 2025The Generalized Skew Spectrum of Graphs
- ICML 2025When do neural networks learn world models?
- NeurIPS 2025$\boldsymbol{\lambda}$-Orthogonality Regularization for Compatible Representation Learning
- NeurIPS 2025Adv-SSL: Adversarial Self-Supervised Representation Learning with Theoretical Guarantees
- NeurIPS 2025Anti-Aliased 2D Gaussian Splatting
- NeurIPS 2025Auto-Compressing Networks
- NeurIPS 2025Beyond Modality Collapse: Representation Blending for Multimodal Dataset Distillation
- NeurIPS 2025Causality-Induced Positional Encoding for Transformer-Based Representation Learning of Non-Sequential Features
- NeurIPS 2025Conditional Representation Learning for Customized Tasks
- NeurIPS 2025Connecting Neural Models Latent Geometries with Relative Geodesic Representations
- NeurIPS 2025DISCO: Disentangled Communication Steering for Large Language Models
- NeurIPS 2025Disentangled Cross-Modal Representation Learning with Enhanced Mutual Supervision
- NeurIPS 2025Disentangled Representation Learning via Modular Compositional Bias
- NeurIPS 2025Equivariance by Contrast: Identifiable Equivariant Embeddings from Unlabeled Finite Group Actions
- NeurIPS 2025EventMG: Efficient Multilevel Mamba-Graph Learning for Spatiotemporal Event Representation
- NeurIPS 2025FORLA: Federated Object-centric Representation Learning with Slot Attention
- NeurIPS 2025GAMMA: Gated Multi-hop Message Passing for Homophily-Agnostic Node Representation in GNNs
- NeurIPS 2025Global Minimizers of Sigmoid Contrastive Loss
- NeurIPS 2025Grids Often Outperform Implicit Neural Representation at Compressing Dense Signals
- NeurIPS 2025H3D-DGS: Exploring Heterogeneous 3D Motion Representation for Deformable 3D Gaussian Splatting
- NeurIPS 2025How Many Tokens Do 3D Point Cloud Transformer Architectures Really Need?
- NeurIPS 2025Kernel-based Equalized Odds: A Quantification of Accuracy-Fairness Trade-off in Fair Representation Learning
- NeurIPS 2025Learning Differential Pyramid Representation for Tone Mapping
- NeurIPS 2025Learning Generalizable Shape Completion with SIM(3) Equivariance
- NeurIPS 2025Learning Without Augmenting: Unsupervised Time Series Representation Learning via Frame Projections
- NeurIPS 2025LLM Interpretability with Identifiable Temporal-Instantaneous Representation
- NeurIPS 2025MaxSup: Overcoming Representation Collapse in Label Smoothing
- NeurIPS 2025Measure-Theoretic Anti-Causal Representation Learning
- NeurIPS 2025Mitigating Spurious Features in Contrastive Learning with Spectral Regularization
- NeurIPS 2025More of the Same: Persistent Representational Harms Under Increased Representation
- NeurIPS 2025NegoCollab: A Common Representation Negotiation Approach for Heterogeneous Collaborative Perception
- NeurIPS 2025On the Value of Cross-Modal Misalignment in Multimodal Representation Learning
- NeurIPS 2025Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning
- NeurIPS 2025PhysioWave: A Multi-Scale Wavelet-Transformer for Physiological Signal Representation
- NeurIPS 2025Point or Line? Using Line-based Representation for Panoptic Symbol Spotting in CAD Drawings
- NeurIPS 2025PoLAR: Polar-Decomposed Low-Rank Adapter Representation
- NeurIPS 2025Provable Sample-Efficient Transfer Learning Conditional Diffusion Models via Representation Learning
- NeurIPS 2025Random Forest Autoencoders for Guided Representation Learning
- NeurIPS 2025REPA Works Until It Doesn’t: Early-Stopped, Holistic Alignment Supercharges Diffusion Training
- NeurIPS 2025Reward-oriented Causal Representation Learning
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"}
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
- 扩散模型 6,900
- 深度学习 · generative models and autoencoders 4,314
- 深度学习 · large language models 2,334
- 深度学习 · self supervised learning 1,958
- 深度学习 · graph neural networks 1,648
- 深度学习 · optimization 953
- 深度学习 · probabilistic methods 637
- 深度学习 · foundation models 536
- 深度学习 · causal inference 316
- 深度学习 · transfer learning 197