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 776 篇，第 2 / 16 页

51. NeurIPS 2023Adversarially Robust Learning with Uncertain Perturbation Sets
52. NeurIPS 2023Aging with GRACE: Lifelong Model Editing with Discrete Key-Value Adaptors
53. NeurIPS 2023Agnostically Learning Single-Index Models using Omnipredictors
54. NeurIPS 2023AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning
55. NeurIPS 2023Aleatoric and Epistemic Discrimination: Fundamental Limits of Fairness Interventions
56. NeurIPS 2023Aligning Optimization Trajectories with Diffusion Models for Constrained Design Generation
57. NeurIPS 2023ALIM: Adjusting Label Importance Mechanism for Noisy Partial Label Learning
58. NeurIPS 2023Ambient Diffusion: Learning Clean Distributions from Corrupted Data
59. NeurIPS 2023An Inductive Bias for Tabular Deep Learning
60. NeurIPS 2023An Information-Theoretic Evaluation of Generative Models in Learning Multi-modal Distributions
61. NeurIPS 2023An Iterative Self-Learning Framework for Medical Domain Generalization
62. NeurIPS 2023Anchor Data Augmentation
63. NeurIPS 2023Anonymous and Copy-Robust Delegations for Liquid Democracy
64. NeurIPS 2023Anonymous Learning via Look-Alike Clustering: A Precise Analysis of Model Generalization
65. NeurIPS 2023Anytime-Competitive Reinforcement Learning with Policy Prior
66. NeurIPS 2023Architecture Matters: Uncovering Implicit Mechanisms in Graph Contrastive Learning
67. NeurIPS 2023ASPEN: Breaking Operator Barriers for Efficient Parallelization of Deep Neural Networks
68. NeurIPS 2023Attention as Implicit Structural Inference
69. NeurIPS 2023Augmentation-Aware Self-Supervision for Data-Efficient GAN Training
70. NeurIPS 2023Augmenting Language Models with Long-Term Memory
71. NeurIPS 2023Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger
72. NeurIPS 2023Autonomous Capability Assessment of Sequential Decision-Making Systems in Stochastic Settings
73. NeurIPS 2023Balancing Risk and Reward: A Batched-Bandit Strategy for Automated Phased Release
74. NeurIPS 2023Banana: Banach Fixed-Point Network for Pointcloud Segmentation with Inter-Part Equivariance
75. NeurIPS 2023Bayesian Metric Learning for Uncertainty Quantification in Image Retrieval
76. NeurIPS 2023Benchmark of Machine Learning Force Fields for Semiconductor Simulations: Datasets, Metrics, and Comparative Analysis
77. NeurIPS 2023Benchmarking and Analyzing 3D-aware Image Synthesis with a Modularized Codebase
78. NeurIPS 2023Benchmarking Encoder-Decoder Architectures for Biplanar X-ray to 3D Bone Shape Reconstruction
79. NeurIPS 2023Beta Diffusion
80. NeurIPS 2023Better Correlation and Robustness: A Distribution-Balanced Self-Supervised Learning Framework for Automatic Dialogue Evaluation
81. NeurIPS 2023Beyond Black-Box Advice: Learning-Augmented Algorithms for MDPs with Q-Value Predictions
82. NeurIPS 2023Beyond Confidence: Reliable Models Should Also Consider Atypicality
83. NeurIPS 2023Beyond Myopia: Learning from Positive and Unlabeled Data through Holistic Predictive Trends
84. NeurIPS 2023Beyond NTK with Vanilla Gradient Descent: A Mean-Field Analysis of Neural Networks with Polynomial Width, Samples, and Time
85. NeurIPS 2023Bilevel Coreset Selection in Continual Learning: A New Formulation and Algorithm
86. NeurIPS 2023BiMatting: Efficient Video Matting via Binarization
87. NeurIPS 2023BIOT: Biosignal Transformer for Cross-data Learning in the Wild
88. NeurIPS 2023Birth of a Transformer: A Memory Viewpoint
89. NeurIPS 2023Bottleneck Structure in Learned Features: Low-Dimension vs Regularity Tradeoff
90. NeurIPS 2023Boundary Guided Learning-Free Semantic Control with Diffusion Models
91. NeurIPS 2023Brain Diffusion for Visual Exploration: Cortical Discovery using Large Scale Generative Models
92. NeurIPS 2023Bridging Discrete and Backpropagation: Straight-Through and Beyond
93. NeurIPS 2023Bridging RL Theory and Practice with the Effective Horizon
94. NeurIPS 2023Bridging the Domain Gap: Self-Supervised 3D Scene Understanding with Foundation Models
95. NeurIPS 2023BubbleML: A Multiphase Multiphysics Dataset and Benchmarks for Machine Learning
96. NeurIPS 2023Building the Bridge of Schrödinger: A Continuous Entropic Optimal Transport Benchmark
97. NeurIPS 2023Bypassing spike sorting: Density-based decoding using spike localization from dense multielectrode probes
98. NeurIPS 2023C-Disentanglement: Discovering Causally-Independent Generative Factors under an Inductive Bias of Confounder
99. NeurIPS 2023Calibrated Stackelberg Games: Learning Optimal Commitments Against Calibrated Agents
100. NeurIPS 2023Canonical normalizing flows for manifold learning

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。