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

Papers per year

Papers per venue

Counts by year and venue

Deep learning · generative models and autoencoders papers by year and venue
YearNeurIPSICLRICMLCVPRTotal
202377678286761,216
2024349174139106768
2025240275275110900
20263493036041741,430

Representative papers

Spread across years and venues so every edition shows up

All Deep learning · generative models and autoencoders papers

275 papers, page 4 of 6

  1. ICLR 2025Looking Backward: Retrospective Backward Synthesis for Goal-Conditioned GFlowNets
  2. ICLR 2025Loss Landscape of Shallow ReLU-like Neural Networks: Stationary Points, Saddle Escape, and Network Embedding
  3. ICLR 2025Lossy Compression with Pretrained Diffusion Models
  4. ICLR 2025Making Transformer Decoders Better Differentiable Indexers
  5. ICLR 2025Manifolds, Random Matrices and Spectral Gaps: The geometric phases of generative diffusion
  6. ICLR 2025MAP: Multi-Human-Value Alignment Palette
  7. ICLR 2025MaRS: A Fast Sampler for Mean Reverting Diffusion based on ODE and SDE Solvers
  8. ICLR 2025MarS: a Financial Market Simulation Engine Powered by Generative Foundation Model
  9. ICLR 2025Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling
  10. ICLR 2025Maximizing the Potential of Synthetic Data: Insights from Random Matrix Theory
  11. ICLR 2025Meissonic: Revitalizing Masked Generative Transformers for Efficient High-Resolution Text-to-Image Synthesis
  12. ICLR 2025MIM-Refiner: A Contrastive Learning Boost from Intermediate Pre-Trained Masked Image Modeling Representations
  13. ICLR 2025Minimal Impact ControlNet: Advancing Multi-ControlNet Integration
  14. ICLR 2025MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
  15. ICLR 2025Mufu: Multilingual Fused Learning for Low-Resource Translation with LLM
  16. ICLR 2025Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
  17. ICLR 2025Multilevel Generative Samplers for Investigating Critical Phenomena
  18. ICLR 2025Multimodal Quantitative Language for Generative Recommendation
  19. ICLR 2025MuPT: A Generative Symbolic Music Pretrained Transformer
  20. ICLR 2025Neural Approximate Mirror Maps for Constrained Diffusion Models
  21. ICLR 2025No Free Lunch: Fundamental Limits of Learning Non-Hallucinating Generative Models
  22. ICLR 2025No Training, No Problem: Rethinking Classifier-Free Guidance for Diffusion Models
  23. ICLR 2025Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation
  24. ICLR 2025Not All Language Model Features Are One-Dimensionally Linear
  25. ICLR 2025Nova: Generative Language Models for Assembly Code with Hierarchical Attention and Contrastive Learning
  26. ICLR 2025NRGBoost: Energy-Based Generative Boosted Trees
  27. ICLR 2025O(d/T) Convergence Theory for Diffusion Probabilistic Models under Minimal Assumptions
  28. ICLR 2025On Statistical Rates of Conditional Diffusion Transformers: Approximation, Estimation and Minimax Optimality
  29. ICLR 2025On the Feature Learning in Diffusion Models
  30. ICLR 2025Once-for-All: Controllable Generative Image Compression with Dynamic Granularity Adaptation
  31. ICLR 2025One Step Diffusion via Shortcut Models
  32. ICLR 2025Optimality and Adaptivity of Deep Neural Features for Instrumental Variable Regression
  33. ICLR 2025Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
  34. ICLR 2025PALMBENCH: A COMPREHENSIVE BENCHMARK OF COMPRESSED LARGE LANGUAGE MODELS ON MOBILE PLATFORMS
  35. ICLR 2025ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models
  36. ICLR 2025PEARL: Parallel Speculative Decoding with Adaptive Draft Length
  37. ICLR 2025PFDiff: Training-Free Acceleration of Diffusion Models Combining Past and Future Scores
  38. ICLR 2025PFGuard: A Generative Framework with Privacy and Fairness Safeguards
  39. ICLR 2025PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
  40. ICLR 2025Physics-Informed Deep Inverse Operator Networks for Solving PDE Inverse Problems
  41. ICLR 2025PN-GAIL: Leveraging Non-optimal Information from Imperfect Demonstrations
  42. ICLR 2025PnP-Flow: Plug-and-Play Image Restoration with Flow Matching
  43. ICLR 2025Port-Hamiltonian Architectural Bias for Long-Range Propagation in Deep Graph Networks
  44. ICLR 2025PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation
  45. ICLR 2025PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
  46. ICLR 2025Probing the Latent Hierarchical Structure of Data via Diffusion Models
  47. ICLR 2025Progressive Compression with Universally Quantized Diffusion Models
  48. ICLR 2025Proteina: Scaling Flow-based Protein Structure Generative Models
  49. ICLR 2025ProtoSnap: Prototype Alignment For Cuneiform Signs
  50. ICLR 2025QA-Calibration of Language Model Confidence Scores

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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.

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