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 13 / 17 页
- ICLR 2024Compositional Generative Inverse Design
- ICLR 2024Concept Bottleneck Generative Models
- ICLR 2024Conditional Variational Diffusion Models
- ICLR 2024Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
- ICLR 2024Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
- ICLR 2024Course Correcting Koopman Representations
- ICLR 2024DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
- ICLR 2024Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
- ICLR 2024Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
- ICLR 2024Delta-AI: Local objectives for amortized inference in sparse graphical models
- ICLR 2024Demystifying Embedding Spaces using Large Language Models
- ICLR 2024DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING
- ICLR 2024Denoising Diffusion Bridge Models
- ICLR 2024Denoising Diffusion Step-aware Models
- ICLR 2024Detecting, Explaining, and Mitigating Memorization in Diffusion Models
- ICLR 2024Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
- ICLR 2024Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
- ICLR 2024DiffusionSat: A Generative Foundation Model for Satellite Imagery
- ICLR 2024DistillSpec: Improving Speculative Decoding via Knowledge Distillation
- ICLR 2024Divide and not forget: Ensemble of selectively trained experts in Continual Learning
- ICLR 2024Don't Play Favorites: Minority Guidance for Diffusion Models
- ICLR 2024DreamLLM: Synergistic Multimodal Comprehension and Creation
- ICLR 2024Efficient and Scalable Graph Generation through Iterative Local Expansion
- ICLR 2024Efficient Integrators for Diffusion Generative Models
- ICLR 2024Elucidating the Exposure Bias in Diffusion Models
- ICLR 2024Emu: Generative Pretraining in Multimodality
- ICLR 2024Energy-guided Entropic Neural Optimal Transport
- ICLR 2024Entropy Coding of Unordered Data Structures
- ICLR 2024Expected flow networks in stochastic environments and two-player zero-sum games
- ICLR 2024Exploring Target Representations for Masked Autoencoders
- ICLR 2024Fusing Models with Complementary Expertise
- ICLR 2024G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
- ICLR 2024Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis
- ICLR 2024Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions
- ICLR 2024GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models
- ICLR 2024GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
- ICLR 2024Generalized Schrödinger Bridge Matching
- ICLR 2024Generating Images with 3D Annotations Using Diffusion Models
- ICLR 2024Generative Adversarial Equilibrium Solvers
- ICLR 2024Generative Human Motion Stylization in Latent Space
- ICLR 2024Generative Judge for Evaluating Alignment
- ICLR 2024Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns
- ICLR 2024Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
- ICLR 2024Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
- ICLR 2024Generative Modeling with Phase Stochastic Bridge
- ICLR 2024Generative Sliced MMD Flows with Riesz Kernels
- ICLR 2024GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules
- ICLR 2024Ghost on the Shell: An Expressive Representation of General 3D Shapes
- ICLR 2024Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
- ICLR 2024H-GAP: Humanoid Control with a Generalist Planner
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。