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 12 / 18 页
- ICML 2025MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
- ICML 2025Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization
- ICML 2025Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
- ICML 2025Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion
- ICML 2025Multilayer Matrix Factorization via Dimension-Reducing Diffusion Variational Inference
- ICML 2025MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
- ICML 2025Near-Optimal Sample Complexity for MDPs via Anchoring
- ICML 2025Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
- ICML 2025NETS: A Non-equilibrium Transport Sampler
- ICML 2025NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones
- ICML 2025Noise Conditional Variational Score Distillation
- ICML 2025Normalizing Flows are Capable Generative Models
- ICML 2025NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
- ICML 2025OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation
- ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
- ICML 2025On the Guidance of Flow Matching
- ICML 2025Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
- ICML 2025Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan
- ICML 2025Perceptually Constrained Precipitation Nowcasting Model
- ICML 2025Physics-Informed Generative Modeling of Wireless Channels
- ICML 2025PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
- ICML 2025PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
- ICML 2025Position: All Current Generative Fidelity and Diversity Metrics are Flawed
- ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
- ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
- ICML 2025Position: Future Research and Challenges Remain Towards AI for Software Engineering
- ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
- ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
- ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
- ICML 2025Position: You Can't Manufacture a NeRF
- ICML 2025Positional Attention: Expressivity and Learnability of Algorithmic Computation
- ICML 2025Privacy Attacks on Image AutoRegressive Models
- ICML 2025Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
- ICML 2025Q-VDiT: Towards Accurate Quantization and Distillation of Video-Generation Diffusion Transformers
- ICML 2025Raising the Bar: Investigating the Values of Large Language Models via Generative Evolving Testing
- ICML 2025REG: Rectified Gradient Guidance for Conditional Diffusion Models
- ICML 2025REINFORCE Adversarial Attacks on Large Language Models: An Adaptive, Distributional, and Semantic Objective
- ICML 2025Rényi Neural Processes
- ICML 2025RestoreGrad: Signal Restoration Using Conditional Denoising Diffusion Models with Jointly Learned Prior
- ICML 2025Rethinking Aleatoric and Epistemic Uncertainty
- ICML 2025Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation
- ICML 2025Revisiting Non-Acyclic GFlowNets in Discrete Environments
- ICML 2025Reward-Guided Iterative Refinement in Diffusion Models at Test-Time with Applications to Protein and DNA Design
- ICML 2025RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers
- ICML 2025Robust Multi-bit Text Watermark with LLM-based Paraphrasers
- ICML 2025Robust Secure Swap: Responsible Face Swap With Persons of Interest Redaction and Provenance Traceability
- ICML 2025RocketKV: Accelerating Long-Context LLM Inference via Two-Stage KV Cache Compression
- ICML 2025S4S: Solving for a Fast Diffusion Model Solver
- ICML 2025SADA: Stability-guided Adaptive Diffusion Acceleration
- ICML 2025SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
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。