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
768 papers, page 10 of 16
- 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
- NeurIPS 2024Conditioning non-linear and infinite-dimensional diffusion processes
- NeurIPS 2024Consistency of Neural Causal Partial Identification
- NeurIPS 2024Constrained Latent Action Policies for Model-Based Offline Reinforcement Learning
- NeurIPS 2024Contrastive-Equivariant Self-Supervised Learning Improves Alignment with Primate Visual Area IT
- NeurIPS 2024ControlMLLM: Training-Free Visual Prompt Learning for Multimodal Large Language Models
- NeurIPS 2024COSMIC: Compress Satellite Image Efficiently via Diffusion Compensation
- NeurIPS 2024CRAG - Comprehensive RAG Benchmark
- NeurIPS 2024Credit Attribution and Stable Compression
- NeurIPS 2024CryoBench: Datasets and Benchmarks for Heterogeneous Cryo-EM Reconstruction
- NeurIPS 2024CryoGEM: Physics-Informed Generative Cryo-Electron Microscopy
- NeurIPS 2024Cryptographic Hardness of Score Estimation
- NeurIPS 2024Ctrl-X: Controlling Structure and Appearance for Text-To-Image Generation Without Guidance
- NeurIPS 2024CV-VAE: A Compatible Video VAE for Latent Generative Video Models
- NeurIPS 2024DAT: Improving Adversarial Robustness via Generative Amplitude Mix-up in Frequency Domain
- NeurIPS 2024Data Attribution for Text-to-Image Models by Unlearning Synthesized Images
- NeurIPS 2024Debiasing Synthetic Data Generated by Deep Generative Models
- NeurIPS 2024DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection
- NeurIPS 2024DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation
- NeurIPS 2024DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform
- NeurIPS 2024DenoiseRep: Denoising Model for Representation Learning
- NeurIPS 2024DiffPhyCon: A Generative Approach to Control Complex Physical Systems
- NeurIPS 2024Diffusion Models With Learned Adaptive Noise
- NeurIPS 2024Diffusion Policy Attacker: Crafting Adversarial Attacks for Diffusion-based Policies
- NeurIPS 2024Diffusion4D: Fast Spatial-temporal Consistent 4D generation via Video Diffusion Models
- NeurIPS 2024DiffusionPDE: Generative PDE-Solving under Partial Observation
- NeurIPS 2024DiMSUM: Diffusion Mamba - A Scalable and Unified Spatial-Frequency Method for Image Generation
- NeurIPS 2024DiP-GO: A Diffusion Pruner via Few-step Gradient Optimization
- NeurIPS 2024Direct3D: Scalable Image-to-3D Generation via 3D Latent Diffusion Transformer
- NeurIPS 2024Distributionally Robust Reinforcement Learning with Interactive Data Collection: Fundamental Hardness and Near-Optimal Algorithms
- NeurIPS 2024Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithm
- NeurIPS 2024Does Reasoning Emerge? Examining the Probabilities of Causation in Large Language Models
Ask about this trend from Claude or Cursor
Connect the Paperlist MCP and your assistant can pull the numbers on this page while you draft a survey, pick a direction or plan a submission: papers per year and venue, growth, the fastest-rising sub-themes and representative papers, shaped around your question.
Copy this prompt into your assistant
Use paperlist to show how Deep learning · generative models and autoencoders papers grew at NeurIPS from 2023 to 2026, and which year jumped the most.
Tool the assistant calls: get_topic_stats {"topic": "dl-generative-models-and-autoencoders"}
Set up Paperlist MCP in two minutes (Claude Code, Cursor, Codex, ChatGPT)
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