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

776 papers, page 14 of 16

651. NeurIPS 2023Spontaneous symmetry breaking in generative diffusion models
652. NeurIPS 2023Squared Neural Families: A New Class of Tractable Density Models
653. NeurIPS 2023SSL4EO-L: Datasets and Foundation Models for Landsat Imagery
654. NeurIPS 2023Stability of Random Forests and Coverage of Random-Forest Prediction Intervals
655. NeurIPS 2023Stability-penalty-adaptive follow-the-regularized-leader: Sparsity, game-dependency, and best-of-both-worlds
656. NeurIPS 2023Stable Diffusion is Unstable
657. NeurIPS 2023StableFDG: Style and Attention Based Learning for Federated Domain Generalization
658. NeurIPS 2023Star-Shaped Denoising Diffusion Probabilistic Models
659. NeurIPS 2023State-space models with layer-wise nonlinearity are universal approximators with exponential decaying memory
660. NeurIPS 2023Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory
661. NeurIPS 2023STEVE-1: A Generative Model for Text-to-Behavior in Minecraft
662. NeurIPS 2023Stochastic Collapse: How Gradient Noise Attracts SGD Dynamics Towards Simpler Subnetworks
663. NeurIPS 2023STORM: Efficient Stochastic Transformer based World Models for Reinforcement Learning
664. NeurIPS 2023Strategic Apple Tasting
665. NeurIPS 2023STREAMER: Streaming Representation Learning and Event Segmentation in a Hierarchical Manner
666. NeurIPS 2023Streaming Factor Trajectory Learning for Temporal Tensor Decomposition
667. NeurIPS 2023StreamNet: Memory-Efficient Streaming Tiny Deep Learning Inference on the Microcontroller
668. NeurIPS 2023Structural Pruning for Diffusion Models
669. NeurIPS 2023Structured Federated Learning through Clustered Additive Modeling
670. NeurIPS 2023Structured Neural Networks for Density Estimation and Causal Inference
671. NeurIPS 2023Structured State Space Models for In-Context Reinforcement Learning
672. NeurIPS 2023StyleGAN knows Normal, Depth, Albedo, and More
673. NeurIPS 2023Swap Agnostic Learning, or Characterizing Omniprediction via Multicalibration
674. NeurIPS 2023SwiFT: Swin 4D fMRI Transformer
675. NeurIPS 2023SwiftSage: A Generative Agent with Fast and Slow Thinking for Complex Interactive Tasks
676. NeurIPS 2023Synthcity: a benchmark framework for diverse use cases of tabular synthetic data
677. NeurIPS 2023Synthetic Experience Replay
678. NeurIPS 2023T2T: From Distribution Learning in Training to Gradient Search in Testing for Combinatorial Optimization
679. NeurIPS 2023TabMT: Generating tabular data with masked transformers
680. NeurIPS 2023Taking the neural sampling code very seriously: A data-driven approach for evaluating generative models of the visual system
681. NeurIPS 2023TART: A plug-and-play Transformer module for task-agnostic reasoning
682. NeurIPS 2023Tartarus: A Benchmarking Platform for Realistic And Practical Inverse Molecular Design
683. NeurIPS 2023Task Arithmetic in the Tangent Space: Improved Editing of Pre-Trained Models
684. NeurIPS 2023Task-aware world model learning with meta weighting via bi-level optimization
685. NeurIPS 2023TaskMet: Task-driven Metric Learning for Model Learning
686. NeurIPS 2023Taylor TD-learning
687. NeurIPS 2023Temporal Conditioning Spiking Latent Variable Models of the Neural Response to Natural Visual Scenes
688. NeurIPS 2023Temporal Dynamic Quantization for Diffusion Models
689. NeurIPS 2023TensorNet: Cartesian Tensor Representations for Efficient Learning of Molecular Potentials
690. NeurIPS 2023Tester-Learners for Halfspaces: Universal Algorithms
691. NeurIPS 2023Text-to-Image Diffusion Models are Zero Shot Classifiers
692. NeurIPS 2023Textually Pretrained Speech Language Models
693. NeurIPS 2023The Adversarial Consistency of Surrogate Risks for Binary Classification
694. NeurIPS 2023The Clock and the Pizza: Two Stories in Mechanistic Explanation of Neural Networks
695. NeurIPS 2023The Contextual Lasso: Sparse Linear Models via Deep Neural Networks
696. NeurIPS 2023The Curious Price of Distributional Robustness in Reinforcement Learning with a Generative Model
697. NeurIPS 2023The Emergence of Essential Sparsity in Large Pre-trained Models: The Weights that Matter
698. NeurIPS 2023The geometry of hidden representations of large transformer models
699. NeurIPS 2023The Pick-to-Learn Algorithm: Empowering Compression for Tight Generalization Bounds and Improved Post-training Performance
700. NeurIPS 2023The probability flow ODE is provably fast

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.