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. ICLR 2025A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
2. ICLR 2025A Geometric Framework for Understanding Memorization in Generative Models
3. ICLR 2025A Large-scale Training Paradigm for Graph Generative Models
4. ICLR 2025A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops
5. ICLR 2025A Watermark for Order-Agnostic Language Models
6. ICLR 2025Accelerating neural network training: An analysis of the AlgoPerf competition
7. ICLR 2025Adaptive teachers for amortized samplers
8. ICLR 2025Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
9. ICLR 2025Adversarial Generative Flow Network for Solving Vehicle Routing Problems
10. ICLR 2025Adversarial Mixup Unlearning
11. ICLR 2025Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI
12. ICLR 2025Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step
13. ICLR 2025Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
14. ICLR 2025An Undetectable Watermark for Generative Image Models
15. ICLR 2025AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
16. ICLR 2025APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
17. ICLR 2025Attributing Culture-Conditioned Generations to Pretraining Corpora
18. ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
19. ICLR 2025Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
20. ICLR 2025Bayesian Regularization of Latent Representation
21. ICLR 2025Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
22. ICLR 2025Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
23. ICLR 2025BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
24. ICLR 2025BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
25. ICLR 2025Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
26. ICLR 2025Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
27. ICLR 2025Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach
28. ICLR 2025Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-grained Control
29. ICLR 2025CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences
30. ICLR 2025Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
31. ICLR 2025Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
32. ICLR 2025CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
33. ICLR 2025Century: A Framework and Dataset for Evaluating Historical Contextualisation of Sensitive Images
34. ICLR 2025CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
35. ICLR 2025ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance
36. ICLR 2025CoInD: Enabling Logical Compositions in Diffusion Models
37. ICLR 2025Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement
38. ICLR 2025Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
39. ICLR 2025Consistency Models Made Easy
40. ICLR 2025Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
41. ICLR 2025Controllable Unlearning for Image-to-Image Generative Models via $\epsilon$-Constrained Optimization
42. ICLR 2025Controlling Language and Diffusion Models by Transporting Activations
43. ICLR 2025Controlling Space and Time with Diffusion Models
44. ICLR 2025Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
45. ICLR 2025Counterfactual Generative Modeling with Variational Causal Inference
46. ICLR 2025CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
47. ICLR 2025Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models
48. ICLR 2025CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction
49. ICLR 2025cryoSPHERE: Single-Particle HEterogeneous REconstruction from cryo EM
50. ICLR 2025Data Shapley in One Training Run

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。