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 4,314 篇，第 38 / 87 页
- ICML 2025Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
- ICML 2025Compelling ReLU Networks to Exhibit Exponentially Many Linear Regions at Initialization and During Training
- ICML 2025Compositional Condition Question Answering in Tabular Understanding
- ICML 2025Compositional Scene Understanding through Inverse Generative Modeling
- ICML 2025Compressed Image Generation with Denoising Diffusion Codebook Models
- ICML 2025Compute Optimal Inference and Provable Amortisation Gap in Sparse Autoencoders
- ICML 2025Concept Reachability in Diffusion Models: Beyond Dataset Constraints
- ICML 2025Concept-Centric Token Interpretation for Vector-Quantized Generative Models
- ICML 2025ConceptAttention: Diffusion Transformers Learn Highly Interpretable Features
- ICML 2025Conditional Diffusion Model with Nonlinear Data Transformation for Time Series Forecasting
- ICML 2025Continuous Semi-Implicit Models
- ICML 2025Continuous Visual Autoregressive Generation via Score Maximization
- ICML 2025Controlled Generation with Equivariant Variational Flow Matching
- ICML 2025D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
- ICML 2025DCTdiff: Intriguing Properties of Image Generative Modeling in the DCT Space
- ICML 2025DeFoG: Discrete Flow Matching for Graph Generation
- ICML 2025Demystifying Cost-Efficiency in LLM Serving over Heterogeneous GPUs
- ICML 2025Density Ratio Estimation with Conditional Probability Paths
- ICML 2025Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
- ICML 2025Differentiable Solver Search for Fast Diffusion Sampling
- ICML 2025Diffuse Everything: Multimodal Diffusion Models on Arbitrary State Spaces
- ICML 2025Diffusion Adversarial Post-Training for One-Step Video Generation
- ICML 2025Diffusion Counterfactual Generation with Semantic Abduction
- ICML 2025Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
- ICML 2025Diffusion Sampling Correction via Approximately 10 Parameters
- ICML 2025Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator
- ICML 2025Direct Motion Models for Assessing Generated Videos
- ICML 2025Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
- ICML 2025Discriminative Finetuning of Generative Large Language Models without Reward Models and Human Preference Data
- ICML 2025Distillation of Discrete Diffusion through Dimensional Correlations
- ICML 2025DiTAR: Diffusion Transformer Autoregressive Modeling for Speech Generation
- ICML 2025Diversity By Design: Leveraging Distribution Matching for Offline Model-Based Optimization
- ICML 2025Does Generation Require Memorization? Creative Diffusion Models using Ambient Diffusion
- ICML 2025EasyInv: Toward Fast and Better DDIM Inversion
- ICML 2025EasyRef: Omni-Generalized Group Image Reference for Diffusion Models via Multimodal LLM
- ICML 2025Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
- ICML 2025Effective and Efficient Masked Image Generation Models
- ICML 2025Efficient Diffusion Models for Symmetric Manifolds
- ICML 2025Efficient Fine-Grained Guidance for Diffusion Model Based Symbolic Music Generation
- ICML 2025Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
- ICML 2025Efficient Molecular Conformer Generation with SO(3)-Averaged Flow Matching and Reflow
- ICML 2025Efficiently Access Diffusion Fisher: Within the Outer Product Span Space
- ICML 2025Elucidating Flow Matching ODE Dynamics via Data Geometry and Denoisers
- ICML 2025Enforcing Latent Euclidean Geometry in Single-Cell VAEs for Manifold Interpolation
- ICML 2025Ensemble Distribution Distillation via Flow Matching
- ICML 2025Epsilon-VAE: Denoising as Visual Decoding
- ICML 2025EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling
- ICML 2025Ergodic Generative Flows
- ICML 2025Explainable Concept Generation through Vision-Language Preference Learning for Understanding Neural Networks' Internal Representations
- ICML 2025Exponential Family Variational Flow Matching for Tabular Data Generation
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。