Deep learning · generative models and autoencoders papers, 2023–2026
Deep learning area: generative_models_and_autoencoders
Scope: NeurIPS, ICLR, ICML and CVPR, 2023–2026. 4,314 papers are tagged with this topic.
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.
Papers per venue
Counts by year and venue
| Year | NeurIPS | ICLR | ICML | CVPR | Total |
|---|---|---|---|---|---|
| 2023 | 776 | 78 | 286 | 76 | 1,216 |
| 2024 | 349 | 174 | 139 | 106 | 768 |
| 2025 | 240 | 275 | 275 | 110 | 900 |
| 2026 | 349 | 303 | 604 | 174 | 1,430 |
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 9 of 17
- ICLR 2025Generalization and Distributed Learning of GFlowNets
- ICLR 2025Generalization in VAE and Diffusion Models: A Unified Information-Theoretic Analysis
- ICLR 2025Generalization through variance: how noise shapes inductive biases in diffusion models
- ICLR 2025Generating Graphs via Spectral Diffusion
- ICLR 2025Generative Adapter: Contextualizing Language Models in Parameters with A Single Forward Pass
- ICLR 2025Generative Classifiers Avoid Shortcut Solutions
- ICLR 2025Generative Inbetweening: Adapting Image-to-Video Models for Keyframe Interpolation
- ICLR 2025Generative Monoculture in Large Language Models
- ICLR 2025Generative Representational Instruction Tuning
- ICLR 2025Generative Verifiers: Reward Modeling as Next-Token Prediction
- ICLR 2025Generator Matching: Generative modeling with arbitrary Markov processes
- ICLR 2025GenSE: Generative Speech Enhancement via Language Models using Hierarchical Modeling
- ICLR 2025GenVP: Generating Visual Puzzles with Contrastive Hierarchical VAEs
- ICLR 2025GenXD: Generating Any 3D and 4D Scenes
- ICLR 2025Geometry of Lightning Self-Attention: Identifiability and Dimension
- ICLR 2025Glauber Generative Model: Discrete Diffusion Models via Binary Classification
- ICLR 2025Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates
- ICLR 2025GMValuator: Similarity-based Data Valuation for Generative Models
- ICLR 2025GOFA: A Generative One-For-All Model for Joint Graph Language Modeling
- ICLR 2025GoodDrag: Towards Good Practices for Drag Editing with Diffusion Models
- ICLR 2025GrabS: Generative Embodied Agent for 3D Object Segmentation without Scene Supervision
- ICLR 2025GTR: Improving Large 3D Reconstruction Models through Geometry and Texture Refinement
- ICLR 2025HaDeMiF: Hallucination Detection and Mitigation in Large Language Models
- ICLR 2025Halton Scheduler for Masked Generative Image Transformer
- ICLR 2025HD-Painter: High-Resolution and Prompt-Faithful Text-Guided Image Inpainting with Diffusion Models
- ICLR 2025Heavy-Tailed Diffusion Models
- ICLR 2025Heavy-Tailed Diffusion with Denoising Levy Probabilistic Models
- ICLR 2025HexGen-2: Disaggregated Generative Inference of LLMs in Heterogeneous Environment
- ICLR 2025HGM³: Hierarchical Generative Masked Motion Modeling with Hard Token Mining
- ICLR 2025Hierarchical Autoregressive Transformers: Combining Byte- and Word-Level Processing for Robust, Adaptable Language Models
- ICLR 2025High-Dimensional Bayesian Optimisation with Gaussian Process Prior Variational Autoencoders
- ICLR 2025High-Quality Joint Image and Video Tokenization with Causal VAE
- ICLR 2025High-quality Text-to-3D Character Generation with SparseCubes and Sparse Transformers.
- ICLR 2025Holistically Evaluating the Environmental Impact of Creating Language Models
- ICLR 2025How Discrete and Continuous Diffusion Meet: Comprehensive Analysis of Discrete Diffusion Models via a Stochastic Integral Framework
- ICLR 2025How DNNs break the Curse of Dimensionality: Compositionality and Symmetry Learning
- ICLR 2025Hybrid Regularization Improves Diffusion-based Inverse Problem Solving
- ICLR 2025IgGM: A Generative Model for Functional Antibody and Nanobody Design
- ICLR 2025Improved Convergence Rate for Diffusion Probabilistic Models
- ICLR 2025Improved Diffusion-based Generative Model with Better Adversarial Robustness
- ICLR 2025Improved Training Technique for Latent Consistency Models
- ICLR 2025Improving Equivariant Networks with Probabilistic Symmetry Breaking
- ICLR 2025Improving Neural Optimal Transport via Displacement Interpolation
- ICLR 2025Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching
- ICLR 2025InstantSplamp: Fast and Generalizable Stenography Framework for Generative Gaussian Splatting
- ICLR 2025Integrative Decoding: Improving Factuality via Implicit Self-consistency
- ICLR 2025JetFormer: An autoregressive generative model of raw images and text
- ICLR 2025Jump Your Steps: Optimizing Sampling Schedule of Discrete Diffusion Models
- ICLR 2025LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusion
- ICLR 2025LARP: Tokenizing Videos with a Learned Autoregressive Generative Prior
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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.
More in Deep Learning
- Diffusion Models 6,900
- Deep learning · large language models 2,334
- Deep learning · self supervised learning 1,958
- Deep learning · graph neural networks 1,648
- Deep learning · optimization 953
- Deep learning · representation learning 802
- Deep learning · probabilistic methods 637
- Deep learning · foundation models 536
- Deep learning · causal inference 316
- Deep learning · transfer learning 197