深度学习 · generative models and autoencoders论文趋势 2023–2026

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。

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 275 篇，第 1 / 6 页

1. ICML 2025A First-order Generative Bilevel Optimization Framework for Diffusion Models
2. ICML 2025A Likelihood Based Approach to Distribution Regression Using Conditional Deep Generative Models
3. ICML 2025A Non-Asymptotic Convergent Analysis for Scored-Based Graph Generative Model via a System of Stochastic Differential Equations
4. ICML 2025A Theory for Conditional Generative Modeling on Multiple Data Sources
5. ICML 2025A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
6. ICML 2025A Variational Framework for Improving Naturalness in Generative Spoken Language Models
7. ICML 2025A Variational Perspective on Generative Protein Fitness Optimization
8. ICML 2025Accelerated Diffusion Models via Speculative Sampling
9. ICML 2025ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
10. ICML 2025AdvI2I: Adversarial Image Attack on Image-to-Image Diffusion Models
11. ICML 2025Aggregation of Dependent Expert Distributions in Multimodal Variational Autoencoders
12. ICML 2025An All-Atom Generative Model for Designing Protein Complexes
13. ICML 2025An Online Learning Approach to Prompt-based Selection of Generative Models and LLMs
14. ICML 2025Analytical Lyapunov Function Discovery: An RL-based Generative Approach
15. ICML 2025Analyze Feature Flow to Enhance Interpretation and Steering in Language Models
16. ICML 2025Angle Domain Guidance: Latent Diffusion Requires Rotation Rather Than Extrapolation
17. ICML 2025Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
18. ICML 2025Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
19. ICML 2025AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
20. ICML 2025Autoencoder-Based Hybrid Replay for Class-Incremental Learning
21. ICML 2025AxBench: Steering LLMs? Even Simple Baselines Outperform Sparse Autoencoders
22. ICML 2025Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
23. ICML 2025Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
24. ICML 2025Benign Overfitting in Token Selection of Attention Mechanism
25. ICML 2025Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
26. ICML 2025Beyond Task-Specific Reasoning: A Unified Conditional Generative Framework for Abstract Visual Reasoning
27. ICML 2025BinauralFlow: A Causal and Streamable Approach for High-Quality Binaural Speech Synthesis with Flow Matching Models
28. ICML 2025Boost-and-Skip: A Simple Guidance-Free Diffusion for Minority Generation
29. ICML 2025Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images?
30. ICML 2025CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
31. ICML 2025Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
32. ICML 2025Categorical Schrödinger Bridge Matching
33. ICML 2025Censor Dependent Variational Inference
34. ICML 2025CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
35. ICML 2025COExpander: Adaptive Solution Expansion for Combinatorial Optimization
36. ICML 2025Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
37. ICML 2025Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
38. ICML 2025Compositional Condition Question Answering in Tabular Understanding
39. ICML 2025Compositional Scene Understanding through Inverse Generative Modeling
40. ICML 2025Compressed Image Generation with Denoising Diffusion Codebook Models
41. ICML 2025Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
42. ICML 2025Concept Reachability in Diffusion Models: Beyond Dataset Constraints
43. ICML 2025Concept-Centric Token Interpretation for Vector-Quantized Generative Models
44. ICML 2025ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
45. ICML 2025Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
46. ICML 2025Continuous Semi-Implicit Models
47. ICML 2025Continuous Visual Autoregressive Generation via Score Maximization
48. ICML 2025Controlled Generation with Equivariant Variational Flow Matching
49. ICML 2025D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
50. ICML 2025DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space

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。