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

776 papers, page 5 of 16

201. NeurIPS 2023Diverse Shape Completion via Style Modulated Generative Adversarial Networks
202. NeurIPS 2023Does Continual Learning Meet Compositionality? New Benchmarks and An Evaluation Framework
203. NeurIPS 2023Domain Adaptive Imitation Learning with Visual Observation
204. NeurIPS 2023Domain Re-Modulation for Few-Shot Generative Domain Adaptation
205. NeurIPS 2023Domain Watermark: Effective and Harmless Dataset Copyright Protection is Closed at Hand
206. NeurIPS 2023DOSE: Diffusion Dropout with Adaptive Prior for Speech Enhancement
207. NeurIPS 2023Double and Single Descent in Causal Inference with an Application to High-Dimensional Synthetic Control
208. NeurIPS 2023Double Gumbel Q-Learning
209. NeurIPS 2023DP-HyPO: An Adaptive Private Framework for Hyperparameter Optimization
210. NeurIPS 2023DP-Mix: Mixup-based Data Augmentation for Differentially Private Learning
211. NeurIPS 2023DropCompute: simple and more robust distributed synchronous training via compute variance reduction
212. NeurIPS 2023DYffusion: A Dynamics-informed Diffusion Model for Spatiotemporal Forecasting
213. NeurIPS 2023Dynamic Pricing and Learning with Bayesian Persuasion
214. NeurIPS 2023Dynamic Prompt Learning: Addressing Cross-Attention Leakage for Text-Based Image Editing
215. NeurIPS 2023Dynamically Masked Discriminator for GANs
216. NeurIPS 2023Dynamics Generalisation in Reinforcement Learning via Adaptive Context-Aware Policies
217. NeurIPS 2023Dynamics of Finite Width Kernel and Prediction Fluctuations in Mean Field Neural Networks
218. NeurIPS 2023EDGI: Equivariant Diffusion for Planning with Embodied Agents
219. NeurIPS 2023Effective Targeted Attacks for Adversarial Self-Supervised Learning
220. NeurIPS 2023Effectively Learning Initiation Sets in Hierarchical Reinforcement Learning
221. NeurIPS 2023Efficient Beam Tree Recursion
222. NeurIPS 2023Efficient Equivariant Transfer Learning from Pretrained Models
223. NeurIPS 2023Efficient Exploration in Continuous-time Model-based Reinforcement Learning
224. NeurIPS 2023Efficient Potential-based Exploration in Reinforcement Learning using Inverse Dynamic Bisimulation Metric
225. NeurIPS 2023Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
226. NeurIPS 2023Efficient Test-Time Adaptation for Super-Resolution with Second-Order Degradation and Reconstruction
227. NeurIPS 2023Efficient Training of Energy-Based Models Using Jarzynski Equality
228. NeurIPS 2023Efficiently incorporating quintuple interactions into geometric deep learning force fields
229. NeurIPS 2023EICIL: Joint Excitatory Inhibitory Cycle Iteration Learning for Deep Spiking Neural Networks
230. NeurIPS 2023Embedding Space Interpolation Beyond Mini-Batch, Beyond Pairs and Beyond Examples
231. NeurIPS 2023Emergent and Predictable Memorization in Large Language Models
232. NeurIPS 2023Encoding Human Behavior in Information Design through Deep Learning
233. NeurIPS 2023Energy Transformer
234. NeurIPS 2023Energy-Based Models for Anomaly Detection: A Manifold Diffusion Recovery Approach
235. NeurIPS 2023Enhancing Adversarial Robustness via Score-Based Optimization
236. NeurIPS 2023Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns
237. NeurIPS 2023Ensemble-based Deep Reinforcement Learning for Vehicle Routing Problems under Distribution Shift
238. NeurIPS 2023Entropy-based Training Methods for Scalable Neural Implicit Samplers
239. NeurIPS 2023Episodic Multi-Task Learning with Heterogeneous Neural Processes
240. NeurIPS 2023Equivariant Flow Matching with Hybrid Probability Transport for 3D Molecule Generation
241. NeurIPS 2023Equivariant Neural Simulators for Stochastic Spatiotemporal Dynamics
242. NeurIPS 2023Equivariant Single View Pose Prediction Via Induced and Restriction Representations
243. NeurIPS 2023Ess-InfoGAIL: Semi-supervised Imitation Learning from Imbalanced Demonstrations
244. NeurIPS 2023Estimating and Controlling for Equalized Odds via Sensitive Attribute Predictors
245. NeurIPS 2023Estimating Causal Effects Identifiable from a Combination of Observations and Experiments
246. NeurIPS 2023Estimating Riemannian Metric with Noise-Contaminated Intrinsic Distance
247. NeurIPS 2023Euler-Lagrange Analysis of Generative Adversarial Networks
248. NeurIPS 2023Evaluating and Inducing Personality in Pre-trained Language Models
249. NeurIPS 2023Evaluating Neuron Interpretation Methods of NLP Models
250. NeurIPS 2023Evaluating the Robustness of Interpretability Methods through Explanation Invariance and Equivariance

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.