深度学习 · generative models and autoencoders论文趋势 2023–2026
ICML/NeurIPS 深度学习方向：generative_models_and_autoencoders
统计范围：NeurIPS、ICLR、ICML、CVPR 四个会议，2023–2026 年，共 4,314 篇被归入该主题的论文。
主要结论
- 深度学习 · generative models and autoencoders论文从 2023 年的 1,216 篇增长到 2026 年的 1,430 篇，三年间扩大到约 1.2 倍。
- NeurIPS 是发深度学习 · generative models and autoencoders论文最多的会议，2023–2026 年共 1,714 篇，占四个会议总量的 40%。
- 交叉方向里涨得最快的是图像生成：同时属于两个主题的论文从 2023 年的 35 篇增至 2026 年的 150 篇。
- 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 2；同组增长最快的扩散模型是 4.1 倍，深度学习 · generative models and autoencoders是 1.2 倍。
各会议论文数
按年份和会议统计
| 年份 | NeurIPS | ICLR | ICML | CVPR | 合计 |
|---|---|---|---|---|---|
| 2023 | 776 | 78 | 286 | 76 | 1,216 |
| 2024 | 349 | 174 | 139 | 106 | 768 |
| 2025 | 240 | 275 | 275 | 110 | 900 |
| 2026 | 349 | 303 | 604 | 174 | 1,430 |
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 2026A Critical $\beta$-Scale for Posterior Collapse in Dirichlet $\beta$-VAEs
- ICML 2026(1D) Ordered Tokens Enable Efficient Test-Time Search
- ICLR 2026``Noisier'’ Noise Contrastive Estimation is (Almost) Maximum Likelihood
- CVPR 2026Anchoring and Rescaling Attention for Semantically Coherent Inbetweening
- NeurIPS 2025Agnostic Learning under Targeted Poisoning: Optimal Rates and the Role of Randomness
- ICML 2025A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
- ICLR 2025A Watermark for Order-Agnostic Language Models
- CVPR 2025DUNE: Distilling a Universal Encoder from Heterogeneous 2D and 3D Teachers
- NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
- ICML 2024A Fixed-Point Approach for Causal Generative Modeling
- ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
- CVPR 2024Decompose-and-Compose: A Compositional Approach to Mitigating Spurious Correlation
- NeurIPS 2023(S)GD over Diagonal Linear Networks: Implicit bias, Large Stepsizes and Edge of Stability
- ICML 2023A Kernelized Stein Discrepancy for Biological Sequences
- ICLR 2023Arbitrary Virtual Try-on Network: Characteristics Representation and Trade-off between Body and Clothing
- CVPR 20233D GAN Inversion With Facial Symmetry Prior
- NeurIPS 2026Action-On-Item Preference Flow: A Shared Event Schema for Predictive and Generative Personalization
- ICML 2026$f$-Trajectory Balance: A Loss Family for Tuning GFlowNets, Generative Models, and LLMs with Off- and On-Policy Data
- ICLR 2026Analyzing and Evaluating Unbiased Language Model Watermark
- CVPR 2026Bidirectional Normalizing Flow From Data to Noise and Back
全部深度学习 · generative models and autoencoders论文
共 4,314 篇，第 17 / 87 页
- ICML 2026Mixtures Closest To A Given Measure: A Semidefinite Programming Approach
- ICML 2026MMD Guidance: Training-Free Distribution Adaptation for Diffusion Models via Maximum Mean Discrepancy Guidance
- ICML 2026Mode Seeking meets Mean Seeking for Fast Long Video Generation
- ICML 2026Modeling Temporal scRNA-seq Data with Latent Gaussian Process and Optimal Transport
- ICML 2026Modelling Attention with Aitchison Geometry: Token Distinguishability and Temperature Scaling
- ICML 2026MolAlign3D: Enhancing Fixed-Dimensional E(3)-Equivariant Latent Space for High-Fidelity 3D Molecular Reconstruction and Editing
- ICML 2026MoLoRA: Composable Specialization via Per-Token Adapter Routing
- ICML 2026Moment Matching Q-Learning
- ICML 2026MoSE: Mixture of Slimmable Experts for Efficient and Adaptive Language Models
- ICML 2026MoST: Mixing Speech and Text with Modality-Aware Mixture of Experts
- ICML 2026Motion Attribution for Video Generation
- ICML 2026Motion-Aware Caching for Efficient Autoregressive Video Generation
- ICML 2026Motion-Residual Conflict-Aware Time Reversal for Generative Inbetweening
- ICML 2026MPFM: Cross Multi-Domain Prototype Flow Matching for Log Anomaly Detection
- ICML 2026MuCO: Generative Peptide Cyclization Empowered by Multi-stage Conformation Optimization
- ICML 2026Multi-marginal temporal Schrödinger Bridge Matching from unpaired data
- ICML 2026Multi-Objective Preference Optimization: Improving Human Alignment of Generative Models
- ICML 2026Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models
- ICML 2026Multimarginal flow matching with optimal transport potentials
- ICML 2026Multipole Semantic Attention: A Fast Approximation of Softmax Attention for Pretraining
- ICML 2026MUSE: Resolving Manifold Misalignment in Visual Tokenization via Topological Orthogonality
- ICML 2026NaviCache: Test-Time Self-Calibration Caching for Video Generation
- ICML 2026Navigating the Energy Landscape of Collaboration: Multi-Agent Communication Graph Generation via Score-Based Diffusion
- ICML 2026Neural Dispersion on Graphs
- ICML 2026Nonparametric Data Attribution for Diffusion Models
- ICML 2026Normalizing Flows with Iterative Denoising
- ICML 2026Offline Reinforcement Learning with Generative Trajectory Policies
- ICML 2026OGPO: Sample Efficient Full-Finetuning of Generative Control Policies
- ICML 2026OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation
- ICML 2026OMP: One-step Meanflow Policy with Directional Alignment
- ICML 2026On the Anisotropy of Score-Based Generative Models
- ICML 2026On the Collapse of Generative Paths: A Criterion and Correction for Diffusion Steering
- ICML 2026On the Fragility of Data Attribution When Learning Is Distributed
- ICML 2026On the Generalization in Topology Optimization via Sensitivity-Conditioned Bernoulli Flow Matching
- ICML 2026On the Relationship Between Activation Outliers and Feature Death in Sparse Autoencoders
- ICML 2026On the Separability of Information in Diffusion Models
- ICML 2026One-step Latent-free Image Generation with Pixel Mean Flows
- ICML 2026One-step Optimal Transport via Regularized Distribution Matching Distillation
- ICML 2026One-Step Residual Shifting Diffusion for Image Super-Resolution via Distillation
- ICML 2026OneSearch: A Preliminary Exploration of the Unified End-to-End Generative Framework for E-commerce Search
- ICML 2026Opportunistic Expert Activation: Batch-Aware Expert Routing for Faster Decode Without Retraining
- ICML 2026Optimal Stopping in Latent Diffusion Models
- ICML 2026Optimality of FSQ Tokens for Continuous Diffusion for Categorical Data with Application to Text-to-Speech
- ICML 2026Optimizing Few-Step Generation with Adaptive Matching Distillation
- ICML 2026Optimizing Visual Generative Models via Distribution-wise Rewards
- ICML 2026Order Matters in Retrosynthesis: Structure-aware Generation via Reaction-Center-Guided Discrete Flow Matching
- ICML 2026Overclocking Electrostatic Generative Models
- ICML 2026OVLR: Efficient, Scalable, and Robust Training via Output-Level Variance-Reduced Likelihood Ratio
- ICML 2026PADS-TAL: Padding-Annealed Diffusion Sampling in Text-Aware Latent Space for Robust and Diverse Text-to-Music Generation
- ICML 2026Parameter Manifold Purification
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 · generative models and autoencoders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-generative-models-and-autoencoders"}
常见问题
- 2023–2026 年四大会议一共有多少篇深度学习 · generative models and autoencoders论文？
- 共 4,314 篇，按年份分别是 2023 年 1,216 篇、2024 年 768 篇、2025 年 900 篇、2026 年 1,430 篇。
- NeurIPS 2026 有多少篇深度学习 · generative models and autoencoders论文？
- NeurIPS 2026 有 349 篇深度学习 · generative models and autoencoders论文，上一届是 240 篇。
- ICLR 2026 有多少篇深度学习 · generative models and autoencoders论文？
- ICLR 2026 有 303 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。
- ICML 2026 有多少篇深度学习 · generative models and autoencoders论文？
- ICML 2026 有 604 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。
- CVPR 2026 有多少篇深度学习 · generative models and autoencoders论文？
- CVPR 2026 有 174 篇深度学习 · generative models and autoencoders论文，上一届是 110 篇。
- 哪个会议的深度学习 · generative models and autoencoders论文最多？
- NeurIPS，2023–2026 年共 1,714 篇。