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

1,216 papers, page 1 of 25

1. CVPR 20233D GAN Inversion With Facial Symmetry Prior
2. CVPR 2023AdaMAE: Adaptive Masking for Efficient Spatiotemporal Learning With Masked Autoencoders
3. CVPR 2023Analyzing and Diagnosing Pose Estimation With Attributions
4. CVPR 2023Bi-Directional Feature Fusion Generative Adversarial Network for Ultra-High Resolution Pathological Image Virtual Re-Staining
5. CVPR 2023CIRCLE: Capture in Rich Contextual Environments
6. CVPR 2023ConvNeXt V2: Co-Designing and Scaling ConvNets With Masked Autoencoders
7. CVPR 2023Cross-GAN Auditing: Unsupervised Identification of Attribute Level Similarities and Differences Between Pretrained Generative Models
8. CVPR 2023Data-Free Knowledge Distillation via Feature Exchange and Activation Region Constraint
9. CVPR 2023Deep Curvilinear Editing: Commutative and Nonlinear Image Manipulation for Pretrained Deep Generative Model
10. CVPR 2023Defining and Quantifying the Emergence of Sparse Concepts in DNNs
11. CVPR 2023DiffSwap: High-Fidelity and Controllable Face Swapping via 3D-Aware Masked Diffusion
12. CVPR 2023Diffusion Video Autoencoders: Toward Temporally Consistent Face Video Editing via Disentangled Video Encoding
13. CVPR 2023DisCoScene: Spatially Disentangled Generative Radiance Fields for Controllable 3D-Aware Scene Synthesis
14. CVPR 2023DropMAE: Masked Autoencoders With Spatial-Attention Dropout for Tracking Tasks
15. CVPR 2023Dynamic Generative Targeted Attacks With Pattern Injection
16. CVPR 2023Enhancing Multiple Reliability Measures via Nuisance-Extended Information Bottleneck
17. CVPR 2023Evading Forensic Classifiers With Attribute-Conditioned Adversarial Faces
18. CVPR 2023FaceLit: Neural 3D Relightable Faces
19. CVPR 2023FIANCEE: Faster Inference of Adversarial Networks via Conditional Early Exits
20. CVPR 2023FlowGrad: Controlling the Output of Generative ODEs With Gradients
21. CVPR 2023GaitGCI: Generative Counterfactual Intervention for Gait Recognition
22. CVPR 2023GALIP: Generative Adversarial CLIPs for Text-to-Image Synthesis
23. CVPR 2023GANHead: Towards Generative Animatable Neural Head Avatars
24. CVPR 2023GD-MAE: Generative Decoder for MAE Pre-Training on LiDAR Point Clouds
25. CVPR 2023Generalizing Dataset Distillation via Deep Generative Prior
26. CVPR 2023Generative Bias for Robust Visual Question Answering
27. CVPR 2023Generative Diffusion Prior for Unified Image Restoration and Enhancement
28. CVPR 2023Generative Semantic Segmentation
29. CVPR 2023Generic-to-Specific Distillation of Masked Autoencoders
30. CVPR 2023High-Fidelity Facial Avatar Reconstruction From Monocular Video With Generative Priors
31. CVPR 2023HOLODIFFUSION: Training a 3D Diffusion Model Using 2D Images
32. CVPR 2023How to Backdoor Diffusion Models?
33. CVPR 2023Implicit 3D Human Mesh Recovery Using Consistency With Pose and Shape From Unseen-View
34. CVPR 2023IS-GGT: Iterative Scene Graph Generation With Generative Transformers
35. CVPR 2023Learning 3D Representations From 2D Pre-Trained Models via Image-to-Point Masked Autoencoders
36. CVPR 2023Learning a Practical SDR-to-HDRTV Up-Conversion Using New Dataset and Degradation Models
37. CVPR 2023Learning Generative Structure Prior for Blind Text Image Super-Resolution
38. CVPR 2023Learning Locally Editable Virtual Humans
39. CVPR 2023Lift3D: Synthesize 3D Training Data by Lifting 2D GAN to 3D Generative Radiance Field
40. CVPR 2023LP-DIF: Learning Local Pattern-Specific Deep Implicit Function for 3D Objects and Scenes
41. CVPR 2023MAGE: MAsked Generative Encoder To Unify Representation Learning and Image Synthesis
42. CVPR 2023MAGVIT: Masked Generative Video Transformer
43. CVPR 2023MAGVLT: Masked Generative Vision-and-Language Transformer
44. CVPR 2023Masked Auto-Encoders Meet Generative Adversarial Networks and Beyond
45. CVPR 2023Masked Autoencoders Enable Efficient Knowledge Distillers
46. CVPR 2023MEGANE: Morphable Eyeglass and Avatar Network
47. CVPR 2023Next3D: Generative Neural Texture Rasterization for 3D-Aware Head Avatars
48. CVPR 2023Objaverse: A Universe of Annotated 3D Objects
49. CVPR 2023ObjectStitch: Object Compositing With Diffusion Model
50. CVPR 2023On the Convergence of IRLS and Its Variants in Outlier-Robust Estimation

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.