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
349 papers, page 1 of 7
- NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
- NeurIPS 20244Diffusion: Multi-view Video Diffusion Model for 4D Generation
- NeurIPS 20244M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities
- NeurIPS 20244Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models
- NeurIPS 2024A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization
- NeurIPS 2024A Closer Look at AUROC and AUPRC under Class Imbalance
- NeurIPS 2024A Functional Extension of Semi-Structured Networks
- NeurIPS 2024A Generative Model of Symmetry Transformations
- NeurIPS 2024A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
- NeurIPS 2024A scalable generative model for dynamical system reconstruction from neuroimaging data
- NeurIPS 2024A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
- NeurIPS 2024A Theoretical Understanding of Self-Correction through In-context Alignment
- NeurIPS 2024A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis
- NeurIPS 2024Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences
- NeurIPS 2024ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
- NeurIPS 2024Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
- NeurIPS 2024Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
- NeurIPS 2024Adversarial Schrödinger Bridge Matching
- NeurIPS 2024AFBench: A Large-scale Benchmark for Airfoil Design
- NeurIPS 2024AirSketch: Generative Motion to Sketch
- NeurIPS 2024Aligning Diffusion Models by Optimizing Human Utility
- NeurIPS 2024An Equivalence Between Static and Dynamic Regret Minimization
- NeurIPS 2024An Image is Worth 32 Tokens for Reconstruction and Generation
- NeurIPS 2024Animate3D: Animating Any 3D Model with Multi-view Video Diffusion
- NeurIPS 2024Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models
- NeurIPS 2024Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
- NeurIPS 2024Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems
- NeurIPS 2024ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
- NeurIPS 2024Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
- NeurIPS 2024Autoregressive Image Generation without Vector Quantization
- NeurIPS 2024Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs
- NeurIPS 2024Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
- NeurIPS 2024Benchmarking Generative Models on Computational Thinking Tests in Elementary Visual Programming
- NeurIPS 2024BERTs are Generative In-Context Learners
- NeurIPS 2024Binding in hippocampal-entorhinal circuits enables compositionality in cognitive maps
- NeurIPS 2024BoNBoN Alignment for Large Language Models and the Sweetness of Best-of-n Sampling
- NeurIPS 2024Boosting Alignment for Post-Unlearning Text-to-Image Generative Models
- NeurIPS 2024BrainBits: How Much of the Brain are Generative Reconstruction Methods Using?
- NeurIPS 2024Bridging Geometric States via Geometric Diffusion Bridge
- NeurIPS 2024Bridging Model-Based Optimization and Generative Modeling via Conservative Fine-Tuning of Diffusion Models
- NeurIPS 2024Bridging OOD Detection and Generalization: A Graph-Theoretic View
- NeurIPS 2024C-GAIL: Stabilizing Generative Adversarial Imitation Learning with Control Theory
- NeurIPS 2024Can Models Learn Skill Composition from Examples?
- NeurIPS 2024Cascade of phase transitions in the training of energy-based models
- NeurIPS 2024Categorical Flow Matching on Statistical Manifolds
- NeurIPS 2024Causal language modeling can elicit search and reasoning capabilities on logic puzzles
- NeurIPS 2024Challenges of Generating Structurally Diverse Graphs
- NeurIPS 2024Classification Diffusion Models: Revitalizing Density Ratio Estimation
- NeurIPS 2024ClavaDDPM: Multi-relational Data Synthesis with Cluster-guided Diffusion Models
- NeurIPS 2024Compositional 3D-aware Video Generation with LLM Director
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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