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 3 / 16 页

101. NeurIPS 2023CAT-Walk: Inductive Hypergraph Learning via Set Walks
102. NeurIPS 2023CBD: A Certified Backdoor Detector Based on Local Dominant Probability
103. NeurIPS 2023Censored Sampling of Diffusion Models Using 3 Minutes of Human Feedback
104. NeurIPS 2023Certification of Distributional Individual Fairness
105. NeurIPS 2023Certified Minimax Unlearning with Generalization Rates and Deletion Capacity
106. NeurIPS 2023Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization
107. NeurIPS 2023CHAMMI: A benchmark for channel-adaptive models in microscopy imaging
108. NeurIPS 2023Chanakya: Learning Runtime Decisions for Adaptive Real-Time Perception
109. NeurIPS 2023Change point detection and inference in multivariate non-parametric models under mixing conditions
110. NeurIPS 2023Characterization and Learning of Causal Graphs with Small Conditioning Sets
111. NeurIPS 2023Characterizing Out-of-Distribution Error via Optimal Transport
112. NeurIPS 2023Cheaply Estimating Inference Efficiency Metrics for Autoregressive Transformer Models
113. NeurIPS 2023Classical Simulation of Quantum Circuits: Parallel Environments and Benchmark
114. NeurIPS 2023ClimateLearn: Benchmarking Machine Learning for Weather and Climate Modeling
115. NeurIPS 2023ClimateSet: A Large-Scale Climate Model Dataset for Machine Learning
116. NeurIPS 2023Closing the Computational-Statistical Gap in Best Arm Identification for Combinatorial Semi-bandits
117. NeurIPS 2023Cluster-aware Semi-supervised Learning: Relational Knowledge Distillation Provably Learns Clustering
118. NeurIPS 2023Cognitive Steering in Deep Neural Networks via Long-Range Modulatory Feedback Connections
119. NeurIPS 2023CoLA: Exploiting Compositional Structure for Automatic and Efficient Numerical Linear Algebra
120. NeurIPS 2023Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise
121. NeurIPS 2023Collaborative Learning via Prediction Consensus
122. NeurIPS 2023Collapsed Inference for Bayesian Deep Learning
123. NeurIPS 2023CoLLAT: On Adding Fine-grained Audio Understanding to Language Models using Token-Level Locked-Language Tuning
124. NeurIPS 2023Combinatorial Group Testing with Selfish Agents
125. NeurIPS 2023Combining Behaviors with the Successor Features Keyboard
126. NeurIPS 2023Communication-Efficient Federated Bilevel Optimization with Global and Local Lower Level Problems
127. NeurIPS 2023Comparing Causal Frameworks: Potential Outcomes, Structural Models, Graphs, and Abstractions
128. NeurIPS 2023Complexity Matters: Rethinking the Latent Space for Generative Modeling
129. NeurIPS 2023Compositional Abilities Emerge Multiplicatively: Exploring Diffusion Models on a Synthetic Task
130. NeurIPS 2023Compositional Generalization from First Principles
131. NeurIPS 2023Compositional Sculpting of Iterative Generative Processes
132. NeurIPS 2023Computational Complexity of Learning Neural Networks: Smoothness and Degeneracy
133. NeurIPS 2023Concept Algebra for (Score-Based) Text-Controlled Generative Models
134. NeurIPS 2023Conditional Adapters: Parameter-efficient Transfer Learning with Fast Inference
135. NeurIPS 2023Conditional independence testing under misspecified inductive biases
136. NeurIPS 2023Conditional score-based diffusion models for Bayesian inference in infinite dimensions
137. NeurIPS 2023Connected Superlevel Set in (Deep) Reinforcement Learning and its Application to Minimax Theorems
138. NeurIPS 2023Connecting Pre-trained Language Model and Downstream Task via Properties of Representation
139. NeurIPS 2023Conservative State Value Estimation for Offline Reinforcement Learning
140. NeurIPS 2023Consistent Diffusion Models: Mitigating Sampling Drift by Learning to be Consistent
141. NeurIPS 2023Contextual Bandits and Imitation Learning with Preference-Based Active Queries
142. NeurIPS 2023Contextually Affinitive Neighborhood Refinery for Deep Clustering
143. NeurIPS 2023Continuous-Time Functional Diffusion Processes
144. NeurIPS 2023Contrastive Moments: Unsupervised Halfspace Learning in Polynomial Time
145. NeurIPS 2023Contrastive Retrospection: honing in on critical steps for rapid learning and generalization in RL
146. NeurIPS 2023Contrastive Sampling Chains in Diffusion Models
147. NeurIPS 2023Contrastive Training of Complex-Valued Autoencoders for Object Discovery
148. NeurIPS 2023Convolutional Neural Operators for robust and accurate learning of PDEs
149. NeurIPS 2023Coop: Memory is not a Commodity
150. NeurIPS 2023CORL: Research-oriented Deep Offline Reinforcement Learning Library

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。