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 900 篇，第 15 / 18 页
- NeurIPS 2025Continuity and Isolation Lead to Doubts or Dilemmas in Large Language Models
- NeurIPS 2025Controllable 3D Molecular Generation for Structure-Based Drug Design Through Bayesian Flow Networks and Gradient Integration
- NeurIPS 2025Controllable Human-centric Keyframe Interpolation with Generative Prior
- NeurIPS 2025CORAL: Disentangling Latent Representations in Long-Tailed Diffusion
- NeurIPS 2025Counteractive RL: Rethinking Core Principles for Efficient and Scalable Deep Reinforcement Learning
- NeurIPS 2025Counterfactual Identifiability via Dynamic Optimal Transport
- NeurIPS 2025Coupling Generative Modeling and an Autoencoder with the Causal Bridge
- NeurIPS 2025Critical Batch Size Revisited: A Simple Empirical Approach to Large-Batch Language Model Training
- NeurIPS 2025DeblurDiff: Real-Word Image Deblurring with Generative Diffusion Models
- NeurIPS 2025DeCaFlow: A deconfounding causal generative model
- NeurIPS 2025Detecting Generated Images by Fitting Natural Image Distributions
- NeurIPS 2025Diff-ICMH: Harmonizing Machine and Human Vision in Image Compression with Generative Prior
- NeurIPS 2025Diffusion Beats Autoregressive in Data-Constrained Settings
- NeurIPS 2025Diffusion Generative Modeling on Lie Group Representations
- NeurIPS 2025Diffusion on Demand: Selective Caching and Modulation for Efficient Generation
- NeurIPS 2025Diffusion Transformers for Imputation: Statistical Efficiency and Uncertainty Quantification
- NeurIPS 2025Dimension-free Score Matching and Time Bootstrapping for Diffusion Models
- NeurIPS 2025Dimensional Collapse in VQVAEs: Evidence and Remedies
- NeurIPS 2025Distributional Autoencoders Know the Score
- NeurIPS 2025Dynamic and Chemical Constraints to Enhance the Molecular Masked Graph Autoencoders
- NeurIPS 2025Efficient Algorithms for Robust and Partial Semi-Discrete Optimal Transport
- NeurIPS 2025Efficient Multimodal Dataset Distillation via Generative Models
- NeurIPS 2025Emergence and Evolution of Interpretable Concepts in Diffusion Models
- NeurIPS 2025Encoder-Decoder Diffusion Language Models for Efficient Training and Inference
- NeurIPS 2025Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling
- NeurIPS 2025Entropic Time Schedulers for Generative Diffusion Models
- NeurIPS 2025Entropy Rectifying Guidance for Diffusion and Flow Models
- NeurIPS 2025Exponential Convergence Guarantees for Iterative Markovian Fitting
- NeurIPS 2025Fine-grained List-wise Alignment for Generative Medication Recommendation
- NeurIPS 2025Flash Invariant Point Attention
- NeurIPS 2025Flow Density Control: Generative Optimization Beyond Entropy-Regularized Fine-Tuning
- NeurIPS 2025FlowDAS: A Stochastic Interpolant-based Framework for Data Assimilation
- NeurIPS 2025FPSAttention: Training-Aware FP8 and Sparsity Co-Design for Fast Video Diffusion
- NeurIPS 2025Fractional Diffusion Bridge Models
- NeurIPS 2025From Information to Generative Exponent: Learning Rate Induces Phase Transitions in SGD
- NeurIPS 2025From Likelihood to Fitness: Improving Variant Effect Prediction in Protein and Genome Language Models
- NeurIPS 2025FuncGenFoil: Airfoil Generation and Editing Model in Function Space
- NeurIPS 2025GenColor: Generative and Expressive Color Enhancement with Pixel-Perfect Texture Preservation
- NeurIPS 2025GeneFlow: Translation of Single-cell Gene Expression to Histopathological Images via Rectified Flow
- NeurIPS 2025Generating Creative Chess Puzzles
- NeurIPS 2025Generating Full-field Evolution of Physical Dynamics from Irregular Sparse Observations
- NeurIPS 2025Generating Physically Sound Designs from Text and a Set of Physical Constraints
- NeurIPS 2025Generation as Search Operator for Test-Time Scaling of Diffusion-based Combinatorial Optimization
- NeurIPS 2025Generative Caching for Structurally Similar Prompts and Responses
- NeurIPS 2025Generative Data Augmentation via Diffusion Distillation, Adversarial Alignment, and Importance Reweighting
- NeurIPS 2025Generative diffusion for perceptron problems: statistical physics analysis and efficient algorithms
- NeurIPS 2025Generative Distribution Embeddings
- NeurIPS 2025Generative Graph Pattern Machine
- NeurIPS 2025Generative Model Inversion Through the Lens of the Manifold Hypothesis
- NeurIPS 2025Generative Modeling of Full-Atom Protein Conformations using Latent Diffusion on Graph Embeddings
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。