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

275 papers, page 1 of 6

1. ICLR 2025A Deep Generative Learning Approach for Two-stage Adaptive Robust Optimization
2. ICLR 2025A Geometric Framework for Understanding Memorization in Generative Models
3. ICLR 2025A Large-scale Training Paradigm for Graph Generative Models
4. ICLR 2025A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops
5. ICLR 2025A Watermark for Order-Agnostic Language Models
6. ICLR 2025Accelerating neural network training: An analysis of the AlgoPerf competition
7. ICLR 2025Adaptive teachers for amortized samplers
8. ICLR 2025Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
9. ICLR 2025Adversarial Generative Flow Network for Solving Vehicle Routing Problems
10. ICLR 2025Adversarial Mixup Unlearning
11. ICLR 2025Adversarial Perturbations Cannot Reliably Protect Artists From Generative AI
12. ICLR 2025Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step
13. ICLR 2025Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
14. ICLR 2025An Undetectable Watermark for Generative Image Models
15. ICLR 2025AnalogGenie: A Generative Engine for Automatic Discovery of Analog Circuit Topologies
16. ICLR 2025APE: Faster and Longer Context-Augmented Generation via Adaptive Parallel Encoding
17. ICLR 2025Attributing Culture-Conditioned Generations to Pretraining Corpora
18. ICLR 2025Balanced Neural ODEs: nonlinear model order reduction and Koopman operator approximations
19. ICLR 2025Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences
20. ICLR 2025Bayesian Regularization of Latent Representation
21. ICLR 2025Be More Diverse than the Most Diverse: Optimal Mixtures of Generative Models via Mixture-UCB Bandit Algorithms
22. ICLR 2025Beyond Squared Error: Exploring Loss Design for Enhanced Training of Generative Flow Networks
23. ICLR 2025BiGR: Harnessing Binary Latent Codes for Image Generation and Improved Visual Representation Capabilities
24. ICLR 2025BinaryDM: Accurate Weight Binarization for Efficient Diffusion Models
25. ICLR 2025Bio-xLSTM: Generative modeling, representation and in-context learning of biological and chemical sequences
26. ICLR 2025Block Diffusion: Interpolating Between Autoregressive and Diffusion Language Models
27. ICLR 2025Broadening Target Distributions for Accelerated Diffusion Models via a Novel Analysis Approach
28. ICLR 2025Cafe-Talk: Generating 3D Talking Face Animation with Multimodal Coarse- and Fine-grained Control
29. ICLR 2025CAKE: Cascading and Adaptive KV Cache Eviction with Layer Preferences
30. ICLR 2025Can Generative AI Solve Your In-Context Learning Problem? A Martingale Perspective
31. ICLR 2025Can Neural Networks Achieve Optimal Computational-statistical Tradeoff? An Analysis on Single-Index Model
32. ICLR 2025CBGBench: Fill in the Blank of Protein-Molecule Complex Binding Graph
33. ICLR 2025Century: A Framework and Dataset for Evaluating Historical Contextualisation of Sensitive Images
34. ICLR 2025CFG++: Manifold-constrained Classifier Free Guidance for Diffusion Models
35. ICLR 2025ClassDiffusion: More Aligned Personalization Tuning with Explicit Class Guidance
36. ICLR 2025CoInD: Enabling Logical Compositions in Diffusion Models
37. ICLR 2025Complementary Label Learning with Positive Label Guessing and Negative Label Enhancement
38. ICLR 2025Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
39. ICLR 2025Consistency Models Made Easy
40. ICLR 2025Continuity-Preserving Convolutional Autoencoders for Learning Continuous Latent Dynamical Models from Images
41. ICLR 2025Controllable Unlearning for Image-to-Image Generative Models via $\epsilon$-Constrained Optimization
42. ICLR 2025Controlling Language and Diffusion Models by Transporting Activations
43. ICLR 2025Controlling Space and Time with Diffusion Models
44. ICLR 2025Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis
45. ICLR 2025Counterfactual Generative Modeling with Variational Causal Inference
46. ICLR 2025CraftRTL: High-quality Synthetic Data Generation for Verilog Code Models with Correct-by-Construction Non-Textual Representations and Targeted Code Repair
47. ICLR 2025Cross-Attention Head Position Patterns Can Align with Human Visual Concepts in Text-to-Image Generative Models
48. ICLR 2025CryoGEN: Generative Energy-based Models for Cryogenic Electron Tomography Reconstruction
49. ICLR 2025cryoSPHERE: Single-Particle HEterogeneous REconstruction from cryo EM
50. ICLR 2025Data Shapley in One Training Run

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.