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

830 papers, page 1 of 17

1. ICLR 2026``Noisier'’ Noise Contrastive Estimation is (Almost) Maximum Likelihood
2. ICLR 2026A Bayesian Nonparametric Framework for Private, Fair, and Balanced Tabular Data Synthesis
3. ICLR 2026A Hidden Semantic Bottleneck in Conditional Embeddings of Diffusion Transformers
4. ICLR 2026A Probabilistic Hard Concept Bottleneck for Steerable Generative Models
5. ICLR 2026A Sharp KL-Convergence Analysis for Diffusion Models under Minimal Assumptions
6. ICLR 2026A Statistical Learning Perspective on Semi-dual Adversarial Neural Optimal Transport Solvers
7. ICLR 2026A Study of Posterior Stability in Time-Series Latent Diffusion
8. ICLR 2026A Unification of Discrete, Gaussian, and Simplicial Diffusion
9. ICLR 2026AbsTopK: Rethinking Sparse Autoencoders For Bidirectional Features
10. ICLR 2026AC-Sampler: Accelerate and Correct Diffusion Sampling with Metropolis-Hastings Algorithm
11. ICLR 2026Accelerated Parallel Tempering via Neural Transports
12. ICLR 2026Adaptive Moments are Surprisingly Effective for Plug-and-Play Diffusion Sampling
13. ICLR 2026AlignFlow: Improving Flow-based Generative Models with Semi-Discrete Optimal Transport
14. ICLR 2026AlphaFlow: Understanding and Improving MeanFlow Models
15. ICLR 2026AlphaSAGE: Structure-Aware Alpha Mining via GFlowNets for Robust Exploration
16. ICLR 2026Amortising Inference and Meta-Learning Priors in Neural Networks
17. ICLR 2026An Ensemble Framework for Unbiased Language Model Watermarking
18. ICLR 2026Analyzing and Evaluating Unbiased Language Model Watermark
19. ICLR 2026Antithetic Noise in Diffusion Models
20. ICLR 2026Any-Order Flexible Length Masked Diffusion
21. ICLR 2026Arbitrary Generative Video Interpolation
22. ICLR 2026ARINBEV: Bird's-Eye View Layout Estimation with Conditional Autoregressive Model
23. ICLR 2026Aurora: Towards Universal Generative Multimodal Time Series Forecasting
24. ICLR 2026Automated Interpretability Metrics Do Not Distinguish Trained and Random Transformers
25. ICLR 2026Automatic Stage Lighting Control: Is it a Rule-Driven Process or Generative Task?
26. ICLR 2026Battery Fault: A Comprehensive Dataset and Benchmark for Battery Fault Diagnosis
27. ICLR 2026Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis
28. ICLR 2026Beyond Ensembles: Simulating All-Atom Protein Dynamics in a Learned Latent Space
29. ICLR 2026Beyond Scattered Acceptance: Fast and Coherent Inference for DLMs via Longest Stable Prefixes
30. ICLR 2026Bi-Lipschitz Autoencoder With Injectivity Guarantee
31. ICLR 2026Bidirectional Predictive Coding
32. ICLR 2026BioTamperNet: Affinity-Guided State-Space Model Detecting Tampered Biomedical Images
33. ICLR 2026BranchGRPO: Stable and Efficient GRPO with Structured Branching in Diffusion Models
34. ICLR 2026Break the Trade-off Between Watermark Strength and Speculative Sampling Efficiency for Language Models
35. ICLR 2026Bridging Generalization Gap of Heterogeneous Federated Clients Using Generative Models
36. ICLR 2026Bridging ML and algorithms: comparison of hyperbolic embeddings
37. ICLR 2026CARE: Covariance-Aware and Rank-Enhanced Decomposition for Enabling Multi-Head Latent Attention
38. ICLR 2026Carré du champ flow matching: better quality-generalisation tradeoff in generative models
39. ICLR 2026Characterizing Deep Research: A Benchmark and Formal Definition
40. ICLR 2026Choices Speak Louder than Questions
41. ICLR 2026CMT: Mid-Training for Efficient Learning of Consistency, Mean Flow, and Flow-Map Models
42. ICLR 2026CO3: CONTRASTING CONCEPTS COMPOSE BETTER
43. ICLR 2026Conditionally Whitened Generative Models for Probabilistic Time Series Forecasting
44. ICLR 2026ConfHit: Conformal Generative Design via Nested Testing
45. ICLR 2026Confident and Adaptive Generative Speech Recognition via Conformal Risk Control
46. ICLR 2026Contact Wasserstein Geodesics for Non-Conservative Schrödinger Bridges
47. ICLR 2026Continual Low-Rank Adapters for LLM-based Generative Recommender Systems
48. ICLR 2026DecompGAIL: Learning Realistic Traffic Behaviors with Decomposed Multi-Agent Generative Adversarial Imitation Learning
49. ICLR 2026Decoupled DMD: CFG Augmentation as the Spear, Distribution Matching as the Shield
50. ICLR 2026Decoupled MeanFlow: Turning Flow Models into Flow Maps for Accelerated Sampling

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.