Deep learning · generative models and autoencoders papers, 2023–2026

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.

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

4,314 papers, page 51 of 87

2501. ICLR 2024Generative Learning for Solving Non-Convex Problem with Multi-Valued Input-Solution Mapping
2502. ICLR 2024Generative Modeling of Regular and Irregular Time Series Data via Koopman VAEs
2503. ICLR 2024Generative Modeling with Phase Stochastic Bridge
2504. ICLR 2024Generative Sliced MMD Flows with Riesz Kernels
2505. ICLR 2024GENOME: Generative Neuro-Symbolic Visual Reasoning by Growing and Reusing Modules
2506. ICLR 2024Ghost on the Shell: An Expressive Representation of General 3D Shapes
2507. ICLR 2024Going Beyond Neural Network Feature Similarity: The Network Feature Complexity and Its Interpretation Using Category Theory
2508. ICLR 2024H-GAP: Humanoid Control with a Generalist Planner
2509. ICLR 2024HiGen: Hierarchical Graph Generative Networks
2510. ICLR 2024How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
2511. ICLR 2024How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
2512. ICLR 2024Human Motion Diffusion as a Generative Prior
2513. ICLR 2024Hybrid Distillation: Connecting Masked Autoencoders with Contrastive Learners
2514. ICLR 2024HypeBoy: Generative Self-Supervised Representation Learning on Hypergraphs
2515. ICLR 2024Idempotence and Perceptual Image Compression
2516. ICLR 2024Idempotent Generative Network
2517. ICLR 2024Improved sampling via learned diffusions
2518. ICLR 2024Improved Techniques for Training Consistency Models
2519. ICLR 2024In-Context Learning Learns Label Relationships but Is Not Conventional Learning
2520. ICLR 2024InfoCon: Concept Discovery with Generative and Discriminative Informativeness
2521. ICLR 2024Inner Classifier-Free Guidance and Its Taylor Expansion for Diffusion Models
2522. ICLR 2024Instructive Decoding: Instruction-Tuned Large Language Models are Self-Refiner from Noisy Instructions
2523. ICLR 2024InstructScene: Instruction-Driven 3D Indoor Scene Synthesis with Semantic Graph Prior
2524. ICLR 2024JoMA: Demystifying Multilayer Transformers via Joint Dynamics of MLP and Attention
2525. ICLR 2024Label-Noise Robust Diffusion Models
2526. ICLR 2024Language Model Cascades: Token-Level Uncertainty And Beyond
2527. ICLR 2024Language-Interfaced Tabular Oversampling via Progressive Imputation and Self-Authentication
2528. ICLR 2024Large Content And Behavior Models To Understand, Simulate, And Optimize Content And Behavior
2529. ICLR 2024Learning Energy Decompositions for Partial Inference in GFlowNets
2530. ICLR 2024Learning Energy-Based Models by Cooperative Diffusion Recovery Likelihood
2531. ICLR 2024Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling
2532. ICLR 2024Leveraging Unpaired Data for Vision-Language Generative Models via Cycle Consistency
2533. ICLR 2024Lewis's Signaling Game as beta-VAE For Natural Word Lengths and Segments
2534. ICLR 2024Lifting Architectural Constraints of Injective Flows
2535. ICLR 2024Light Schrödinger Bridge
2536. ICLR 2024Lipschitz Singularities in Diffusion Models
2537. ICLR 2024LitCab: Lightweight Language Model Calibration over Short- and Long-form Responses
2538. ICLR 2024Localizing and Editing Knowledge In Text-to-Image Generative Models
2539. ICLR 2024Long-tailed Diffusion Models with Oriented Calibration
2540. ICLR 2024LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
2541. ICLR 2024Machine Unlearning for Image-to-Image Generative Models
2542. ICLR 2024Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
2543. ICLR 2024Manifold Diffusion Fields
2544. ICLR 2024Manifold Preserving Guided Diffusion
2545. ICLR 2024Masked Autoencoders with Multi-Window Local-Global Attention Are Better Audio Learners
2546. ICLR 2024MBR and QE Finetuning: Training-time Distillation of the Best and Most Expensive Decoding Methods
2547. ICLR 2024MiniLLM: Knowledge Distillation of Large Language Models
2548. ICLR 2024Model Tells You What to Discard: Adaptive KV Cache Compression for LLMs
2549. ICLR 2024Modelling complex vector drawings with stroke-clouds
2550. ICLR 2024Multi-modal Gaussian Process Variational Autoencoders for Neural and Behavioral Data

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.