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 1,714 篇，第 3 / 35 页

101. NeurIPS 2026Fast and Consistent Structure Learning in Graphical Models via Approximate Cross-Validation
102. NeurIPS 2026FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model
103. NeurIPS 2026Ferrogen: Generative Pipeline for Guided Search of Novel Ferroelectric Material for Logic and Memory
104. NeurIPS 2026Few-Step Cofolding with All-Atom Flow Maps
105. NeurIPS 2026Fine-Tuning Improves Information Conveyance in Language Models
106. NeurIPS 2026Fix the Structural Bottleneck: Context Compression via Explicit Information Transmission
107. NeurIPS 2026Fixed-Point Masked Generative Modeling
108. NeurIPS 2026Flowette: Flow Matching with Graphette Priors for Graph Generation
109. NeurIPS 2026FluxLite: Inference-Time Proposal Control for Discrete Diffusion Models
110. NeurIPS 2026FoMo: Forking Moment in Generative Trajectory as a Perceptual Distance
111. NeurIPS 2026Frank-LoRA: Federated Rank-Aware LoRA for Fine-Tuning Large Models
112. NeurIPS 2026From Baselines to Transport Geodesics: Axiomatic Attribution via Optimal Generative Flows
113. NeurIPS 2026From Jumps to Signatures: a Generative Method for Temporal Point Processes
114. NeurIPS 2026From Static Geometry to Dynamical Singularity: Detecting Memorization in Diffusion Models via Score Evolution
115. NeurIPS 2026Frontier-Eng: Benchmarking Self-Evolving Agents on Real-World Engineering with Generative Optimization
116. NeurIPS 2026Full-Sequence Masked Diffusion for Generative Recommendation
117. NeurIPS 2026G2Fusion: Geometric-to-Generative Image Fusion via Registration-Restoration Evolution
118. NeurIPS 2026GazeFlow: From Human Gaze Behavior to Generative Egocentric Gaze Prediction
119. NeurIPS 2026GenEnv: Difficulty-Aligned Co-Evolution Between LLM Agents and Environment Simulators
120. NeurIPS 2026Generalization Dynamics of Linear Diffusion Models
121. NeurIPS 2026Generalized Wasserstein Flow Matching: Transport Plans, Everywhere, All at Once
122. NeurIPS 2026Generating Financial Time Series by Matching Random Convolutional Features
123. NeurIPS 2026Generative Active Learning via Bayesian Acquisition for Improving the Efficiency of Synthetic Data
124. NeurIPS 2026Generative Actor-Critic with Soft Bridge Policies
125. NeurIPS 2026Generative Conformal Prediction with Optimized Coverage Allocation
126. NeurIPS 2026Generative Cross-Entropy: A Strictly Proper Loss for Data-Efficient Classification
127. NeurIPS 2026Generative Modeling under Non-Monotone MAR Missingness via Approximate Wasserstein Gradient Flows
128. NeurIPS 2026Generative Modeling via Drifting
129. NeurIPS 2026Generative Molecular Morphing for Flexible-Size Design via Unbalanced Optimal Transport
130. NeurIPS 2026GenRec: Knowing Where to Reconstruct and Where to Generate
131. NeurIPS 2026GenRecon: Bridging Generative Priors for Multi-View 3D Scene Reconstruction
132. NeurIPS 2026Geometric Velocity Regularity for Flow Matching on Manifold-Concentrated Data
133. NeurIPS 2026gfnx: Fast and Scalable Library for Generative Flow Networks in JAX
134. NeurIPS 2026GPA: Generative Population Annealing for Test-Time Sequence Design with Pretrained Generative Models
135. NeurIPS 2026Gradient Routing Localizes and Removes Unintended Behaviors in RL
136. NeurIPS 2026Guaranteed Jailbreaking Defense via Disrupt-and-Rectify Smoothing
137. NeurIPS 2026HaNDF: Object-Conditioned Geometric Neural Hand Distance Fields
138. NeurIPS 2026HERO: Improving the Reliability and Sensitivity of Generative Model Evaluation Using Historical Data
139. NeurIPS 2026Hit Expansion via Localized Exploration of Synthesizable Chemical Space
140. NeurIPS 2026Horizontal Diffusion Models: Score-based Generative Modeling on Frame-Connection Geometry
141. NeurIPS 2026Hypergraph Generation via Structured Stochastic Diffusion
142. NeurIPS 2026HyperTransport: Amortized Conditioning of T2I Generative Models
143. NeurIPS 2026HyperVQ: Enabling Hyperprior Entropy Modeling for VQ-Based Generative Image Compression
144. NeurIPS 2026Idempotency Exposes Consistency Problems in Sparse Autoencoders
145. NeurIPS 2026Imagine, Don't Narrate: The Generative Bottleneck in World Models of Interaction Dynamics
146. NeurIPS 2026Improving Function Space Flow Matching with Kernel Optimal Transport
147. NeurIPS 2026Incorporating Hierarchical Semantics in Sparse Autoencoder Architectures
148. NeurIPS 2026Inference-Time Refinement Closes the Synthetic-Real Gap in Tabular Diffusion
149. NeurIPS 2026Inference-Time Self-Aligned Drifting for Few-Step Flow Matching
150. NeurIPS 2026Inferotemporal Cortex Collaborates Before It Codes: Non-Serial Inter-Area Synergy in the Macaque Ventral Stream

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。