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 2 of 6

51. ICLR 2025Data Unlearning in Diffusion Models
52. ICLR 2025Deep Compression Autoencoder for Efficient High-Resolution Diffusion Models
53. ICLR 2025Deep Incomplete Multi-view Learning via Cyclic Permutation of VAEs
54. ICLR 2025DiffPuter: Empowering Diffusion Models for Missing Data Imputation
55. ICLR 2025Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
56. ICLR 2025Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
57. ICLR 2025Diffusion Feedback Helps CLIP See Better
58. ICLR 2025Diffusion Models are Evolutionary Algorithms
59. ICLR 2025Diffusion Models as Cartoonists: The Curious Case of High Density Regions
60. ICLR 2025Diffusion-based Decoupled Deterministic and Uncertain Framework for Probabilistic Multivariate Time Series Forecasting
61. ICLR 2025Diffusion$^2$: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models
62. ICLR 2025Discrete Copula Diffusion
63. ICLR 2025Discrete Distribution Networks
64. ICLR 2025Distributed Speculative Inference (DSI): Speculation Parallelism for Provably Faster Lossless Language Model Inference
65. ICLR 2025Do WGANs succeed because they minimize the Wasserstein Distance? Lessons from Discrete Generators
66. ICLR 2025DreamCatalyst: Fast and High-Quality 3D Editing via Controlling Editability and Identity Preservation
67. ICLR 2025Dynamic Assortment Selection and Pricing with Censored Preference Feedback
68. ICLR 2025Dynamic Diffusion Transformer
69. ICLR 2025Dynamic Negative Guidance of Diffusion Models
70. ICLR 2025Dynamical Diffusion: Learning Temporal Dynamics with Diffusion Models
71. ICLR 2025Dysca: A Dynamic and Scalable Benchmark for Evaluating Perception Ability of LVLMs
72. ICLR 2025Easing Training Process of Rectified Flow Models Via Lengthening Inter-Path Distance
73. ICLR 2025Efficient Dictionary Learning with Switch Sparse Autoencoders
74. ICLR 2025Efficient Inference for Large Language Model-based Generative Recommendation
75. ICLR 2025Efficient Perplexity Bound and Ratio Matching in Discrete Diffusion Language Models
76. ICLR 2025Eliminating Oversaturation and Artifacts of High Guidance Scales in Diffusion Models
77. ICLR 2025Elucidating the Preconditioning in Consistency Distillation
78. ICLR 2025Enhanced Diffusion Sampling via Extrapolation with Multiple ODE Solutions
79. ICLR 2025FaceShot: Bring Any Character into Life
80. ICLR 2025Fantastic Targets for Concept Erasure in Diffusion Models and Where To Find Them
81. ICLR 2025Fast training and sampling of Restricted Boltzmann Machines
82. ICLR 2025Fast Uncovering of Protein Sequence Diversity from Structure
83. ICLR 2025Faster Cascades via Speculative Decoding
84. ICLR 2025Faster Diffusion Sampling with Randomized Midpoints: Sequential and Parallel
85. ICLR 2025Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
86. ICLR 2025Feedback Schrödinger Bridge Matching
87. ICLR 2025Field-DiT: Diffusion Transformer on Unified Video, 3D, and Game Field Generation
88. ICLR 2025FIG: Flow with Interpolant Guidance for Linear Inverse Problems
89. ICLR 2025Flash Inference: Near Linear Time Inference for Long Convolution Sequence Models and Beyond
90. ICLR 2025FlexCAD: Unified and Versatile Controllable CAD Generation with Fine-tuned Large Language Models
91. ICLR 2025Flow matching achieves almost minimax optimal convergence
92. ICLR 2025Fluid: Scaling Autoregressive Text-to-image Generative Models with Continuous Tokens
93. ICLR 2025Forte : Finding Outliers with Representation Typicality Estimation
94. ICLR 2025Fragment and Geometry Aware Tokenization of Molecules for Structure-Based Drug Design Using Language Models
95. ICLR 2025From Search to Sampling: Generative Models for Robust Algorithmic Recourse
96. ICLR 2025Fugatto 1: Foundational Generative Audio Transformer Opus 1
97. ICLR 2025GANDALF: Generative AttentioN based Data Augmentation and predictive modeLing Framework for personalized cancer treatment
98. ICLR 2025Generalization and Distributed Learning of GFlowNets
99. ICLR 2025Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
100. ICLR 2025Generalization through variance: how noise shapes inductive biases in diffusion models

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.