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
1,304 papers, page 16 of 27
- ICML 2025Learning Latent Graph Structures and their Uncertainty
- ICML 2025Learning Monotonic Probabilities with a Generative Cost Model
- ICML 2025Learning Multi-Level Features with Matryoshka Sparse Autoencoders
- ICML 2025Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
- ICML 2025Learning to Match Unpaired Data with Minimum Entropy Coupling
- ICML 2025Learning to Quantize for Training Vector-Quantized Networks
- ICML 2025Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
- ICML 2025LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
- ICML 2025LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
- ICML 2025Low-Rank Adapting Models for Sparse Autoencoders
- ICML 2025Masked Autoencoders Are Effective Tokenizers for Diffusion Models
- ICML 2025Masked Generative Nested Transformers with Decode Time Scaling
- ICML 2025MDDM: Practical Message-Driven Generative Image Steganography Based on Diffusion Models
- ICML 2025Measuring Diversity: Axioms and Challenges
- ICML 2025Mechanisms of Projective Composition of Diffusion Models
- ICML 2025MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
- ICML 2025MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
- ICML 2025MissScore: High-Order Score Estimation in the Presence of Missing Data
- ICML 2025MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES
- ICML 2025MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
- ICML 2025Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization
- ICML 2025Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
- ICML 2025Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion
- ICML 2025Multilayer Matrix Factorization via Dimension-Reducing Diffusion Variational Inference
- ICML 2025MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
- ICML 2025Near-Optimal Sample Complexity for MDPs via Anchoring
- ICML 2025Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
- ICML 2025NETS: A Non-equilibrium Transport Sampler
- ICML 2025NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones
- ICML 2025Noise Conditional Variational Score Distillation
- ICML 2025Normalizing Flows are Capable Generative Models
- ICML 2025NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
- ICML 2025OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation
- ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
- ICML 2025On the Guidance of Flow Matching
- ICML 2025Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
- ICML 2025Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan
- ICML 2025Perceptually Constrained Precipitation Nowcasting Model
- ICML 2025Physics-Informed Generative Modeling of Wireless Channels
- ICML 2025PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
- ICML 2025PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
- ICML 2025Position: All Current Generative Fidelity and Diversity Metrics are Flawed
- ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
- ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
- ICML 2025Position: Future Research and Challenges Remain Towards AI for Software Engineering
- ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
- ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
- ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
- ICML 2025Position: You Can't Manufacture a NeRF
- ICML 2025Positional Attention: Expressivity and Learnability of Algorithmic Computation
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