Deep learning · generative models and autoencoders papers, 2023–2026

Key findings

• Deep learning · generative models and autoencoders went from 1,216 papers in 2023 to 1,430 in 2026, roughly 1.2x in three years.
• NeurIPS publishes the most Deep learning · generative models and autoencoders work: 1,714 papers from 2023 to 2026, 40% of the four-venue total.
• The fastest-growing overlap is with Image Generation: papers tagged with both rose from 35 in 2023 to 150 in 2026.
• Among the 11 topics under Deep Learning, it ranks #2 by 2026 paper count; the fastest grower in the group, Diffusion Models, is up 4.1x versus 1.2x here.

Representative papers

Spread across years and venues so every edition shows up

• 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

All Deep learning · generative models and autoencoders papers

768 papers, page 4 of 16

151. ICLR 2024Efficient and Scalable Graph Generation through Iterative Local Expansion
152. ICLR 2024Efficient Integrators for Diffusion Generative Models
153. ICLR 2024Elucidating the Exposure Bias in Diffusion Models
154. ICLR 2024Emu: Generative Pretraining in Multimodality
155. ICLR 2024Energy-guided Entropic Neural Optimal Transport
156. ICLR 2024Entropy Coding of Unordered Data Structures
157. ICLR 2024Expected flow networks in stochastic environments and two-player zero-sum games
158. ICLR 2024Exploring Target Representations for Masked Autoencoders
159. ICLR 2024Fusing Models with Complementary Expertise
160. ICLR 2024G$^2$N$^2$ : Weisfeiler and Lehman go grammatical
161. ICLR 2024Gaining Wisdom from Setbacks: Aligning Large Language Models via Mistake Analysis
162. ICLR 2024Gen-Z: Generative Zero-Shot Text Classification with Contextualized Label Descriptions
163. ICLR 2024GenCorres: Consistent Shape Matching via Coupled Implicit-Explicit Shape Generative Models
164. ICLR 2024GeneOH Diffusion: Towards Generalizable Hand-Object Interaction Denoising via Denoising Diffusion
165. ICLR 2024Generalized Schrödinger Bridge Matching
166. ICLR 2024Generating Images with 3D Annotations Using Diffusion Models
167. ICLR 2024Generative Adversarial Equilibrium Solvers
168. ICLR 2024Generative Human Motion Stylization in Latent Space
169. ICLR 2024Generative Judge for Evaluating Alignment
170. ICLR 2024Generative Learning for Financial Time Series with Irregular and Scale-Invariant Patterns
171. ICLR 2024Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
172. ICLR 2024Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
173. ICLR 2024Generative Modeling with Phase Stochastic Bridge
174. ICLR 2024Generative Sliced MMD Flows with Riesz Kernels
175. ICLR 2024GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules
176. ICLR 2024Ghost on the Shell: An Expressive Representation of General 3D Shapes
177. ICLR 2024Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
178. ICLR 2024H-GAP: Humanoid Control with a Generalist Planner
179. ICLR 2024HiGen: Hierarchical Graph Generative Networks
180. ICLR 2024How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
181. ICLR 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
182. ICLR 2024Human Motion Diffusion as a Generative Prior
183. ICLR 2024Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
184. ICLR 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
185. ICLR 2024Idempotence and Perceptual Image Compression
186. ICLR 2024Idempotent Generative Network
187. ICLR 2024Improved sampling via learned diffusions
188. ICLR 2024Improved Techniques for Training Consistency Models
189. ICLR 2024In-Context Learning Learns Label Relationships but Is Not Conventional Learning
190. ICLR 2024InfoCon: Concept Discovery with Generative and Discriminative Informativeness
191. ICLR 2024Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
192. ICLR 2024Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
193. ICLR 2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
194. ICLR 2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention
195. ICLR 2024Label-Noise Robust Diffusion Models
196. ICLR 2024Language Model Cascades: Token-Level Uncertainty And Beyond
197. ICLR 2024Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication
198. ICLR 2024Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior
199. ICLR 2024Learning Energy Decompositions for Partial Inference in GFlowNets
200. ICLR 2024Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood

FAQ

How many Deep learning · generative models and autoencoders papers were published at NeurIPS, ICLR, ICML and CVPR from 2023 to 2026?

4,314 in total: 1,216 in 2023, 768 in 2024, 900 in 2025, 1,430 in 2026.

How many Deep learning · generative models and autoencoders papers are at NeurIPS 2026?

NeurIPS 2026 has 349 Deep learning · generative models and autoencoders papers, versus 240 the year before.

How many Deep learning · generative models and autoencoders papers are at ICLR 2026?

ICLR 2026 has 303 Deep learning · generative models and autoencoders papers, versus 275 the year before.

How many Deep learning · generative models and autoencoders papers are at ICML 2026?

ICML 2026 has 604 Deep learning · generative models and autoencoders papers, versus 275 the year before.

How many Deep learning · generative models and autoencoders papers are at CVPR 2026?

CVPR 2026 has 174 Deep learning · generative models and autoencoders papers, versus 110 the year before.

Which conference publishes the most Deep learning · generative models and autoencoders papers?

NeurIPS, with 1,714 papers from 2023 to 2026.