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 830 篇，第 10 / 17 页
- ICLR 2025Layout-your-3D: Controllable and Precise 3D Generation with 2D Blueprint
- ICLR 2025Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
- ICLR 2025Linear combinations of latents in generative models: subspaces and beyond
- ICLR 2025Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
- ICLR 2025Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
- ICLR 2025Lossy Compression with Pretrained Diffusion Models
- ICLR 2025Making Transformer Decoders Better Differentiable Indexers
- ICLR 2025Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion
- ICLR 2025MAP: Multi-Human-Value Alignment Palette
- ICLR 2025MaRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers
- ICLR 2025MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
- ICLR 2025Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling
- ICLR 2025Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
- ICLR 2025Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
- ICLR 2025MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations
- ICLR 2025Minimal Impact ControlNet: Advancing Multi-ControlNet Integration
- ICLR 2025MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
- ICLR 2025Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM
- ICLR 2025Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
- ICLR 2025Multilevel Generative Samplers for Investigating Critical Phenomena
- ICLR 2025Multimodal Quantitative Language for Generative Recommendation
- ICLR 2025MuPT: A Generative Symbolic Music Pretrained Transformer
- ICLR 2025Neural Approximate Mirror Maps for Constrained Diffusion Models
- ICLR 2025No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
- ICLR 2025No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models
- ICLR 2025Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
- ICLR 2025Not All Language Model Features Are One-Dimensionally Linear
- ICLR 2025Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning
- ICLR 2025NRGBoost: Energy-Based Generative Boosted Trees
- ICLR 2025O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions
- ICLR 2025On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality
- ICLR 2025On the Feature Learning in Diffusion Models
- ICLR 2025Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation
- ICLR 2025One Step Diffusion via Shortcut Models
- ICLR 2025Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
- ICLR 2025Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
- ICLR 2025PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS
- ICLR 2025ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models
- ICLR 2025PEARL: Parallel Speculative Decoding with Adaptive Draft Length
- ICLR 2025PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
- ICLR 2025PFGuard: A Generative Framework with Privacy and Fairness Safeguards
- ICLR 2025PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
- ICLR 2025Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems
- ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
- ICLR 2025PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
- ICLR 2025Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
- ICLR 2025PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
- ICLR 2025PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
- ICLR 2025Probing the Latent Hierarchical Structure of Data via Diffusion Models
- ICLR 2025Progressive Compression with Universally Quantized Diffusion Models
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。