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

174 papers, page 1 of 4

1. ICLR 2024$\alpha$TC-VAE: On the relationship between Disentanglement and Diversity
2. ICLR 2024$\infty$-Diff: Infinite Resolution Diffusion with Subsampled Mollified States
3. ICLR 2024$t^3$-Variational Autoencoder: Learning Heavy-tailed Data with Student's t and Power Divergence
4. ICLR 2024A Flexible Generative Model for Heterogeneous Tabular EHR with Missing Modality
5. ICLR 2024A Simple and Scalable Representation for Graph Generation
6. ICLR 2024A Statistical Analysis of Wasserstein Autoencoders for Intrinsically Low-dimensional Data
7. ICLR 2024A Variational Perspective on Solving Inverse Problems with Diffusion Models
8. ICLR 2024AgentVerse: Facilitating Multi-Agent Collaboration and Exploring Emergent Behaviors
9. ICLR 2024AlpaGasus: Training a Better Alpaca with Fewer Data
10. ICLR 2024Amortizing intractable inference in large language models
11. ICLR 2024Analysis of Learning a Flow-based Generative Model from Limited Sample Complexity
12. ICLR 2024Analyzing and Improving Optimal-Transport-based Adversarial Networks
13. ICLR 2024Are Bert Family Good Instruction Followers? A Study on Their Potential And Limitations
14. ICLR 2024Batch Calibration: Rethinking Calibration for In-Context Learning and Prompt Engineering
15. ICLR 2024BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference
16. ICLR 2024Beating Price of Anarchy and Gradient Descent without Regret in Potential Games
17. ICLR 2024Bellman Optimal Stepsize Straightening of Flow-Matching Models
18. ICLR 2024Bespoke Solvers for Generative Flow Models
19. ICLR 2024Beyond Vanilla Variational Autoencoders: Detecting Posterior Collapse in Conditional and Hierarchical Variational Autoencoders
20. ICLR 2024Boosting of Thoughts: Trial-and-Error Problem Solving with Large Language Models
21. ICLR 2024CADS: Unleashing the Diversity of Diffusion Models through Condition-Annealed Sampling
22. ICLR 2024Compose and Conquer: Diffusion-Based 3D Depth Aware Composable Image Synthesis
23. ICLR 2024Compositional Generative Inverse Design
24. ICLR 2024Concept Bottleneck Generative Models
25. ICLR 2024Conditional Variational Diffusion Models
26. ICLR 2024Consistency Trajectory Models: Learning Probability Flow ODE Trajectory of Diffusion
27. ICLR 2024Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
28. ICLR 2024Course Correcting Koopman Representations
29. ICLR 2024DDMI: Domain-agnostic Latent Diffusion Models for Synthesizing High-Quality Implicit Neural Representations
30. ICLR 2024Decomposed Diffusion Sampler for Accelerating Large-Scale Inverse Problems
31. ICLR 2024Deep Generative Clustering with Multimodal Diffusion Variational Autoencoders
32. ICLR 2024Delta-AI: Local objectives for amortized inference in sparse graphical models
33. ICLR 2024Demystifying Embedding Spaces using Large Language Models
34. ICLR 2024DENEVIL: TOWARDS DECIPHERING AND NAVIGATING THE ETHICAL VALUES OF LARGE LANGUAGE MODELS VIA INSTRUCTION LEARNING
35. ICLR 2024Denoising Diffusion Bridge Models
36. ICLR 2024Denoising Diffusion Step-aware Models
37. ICLR 2024Detecting, Explaining, and Mitigating Memorization in Diffusion Models
38. ICLR 2024Dichotomy of Early and Late Phase Implicit Biases Can Provably Induce Grokking
39. ICLR 2024Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
40. ICLR 2024DiffusionSat: A Generative Foundation Model for Satellite Imagery
41. ICLR 2024DistillSpec: Improving Speculative Decoding via Knowledge Distillation
42. ICLR 2024Divide and not forget: Ensemble of selectively trained experts in Continual Learning
43. ICLR 2024Don't Play Favorites: Minority Guidance for Diffusion Models
44. ICLR 2024DreamLLM: Synergistic Multimodal Comprehension and Creation
45. ICLR 2024Efficient and Scalable Graph Generation through Iterative Local Expansion
46. ICLR 2024Efficient Integrators for Diffusion Generative Models
47. ICLR 2024Elucidating the Exposure Bias in Diffusion Models
48. ICLR 2024Emu: Generative Pretraining in Multimodality
49. ICLR 2024Energy-guided Entropic Neural Optimal Transport
50. ICLR 2024Entropy Coding of Unordered Data Structures

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.