深度学习 · generative models and autoencoders论文趋势 2023–2026

主要结论

• 深度学习 · generative models and autoencoders论文从 2023 年的 1,216 篇增长到 2026 年的 1,430 篇，三年间扩大到约 1.2 倍。
• NeurIPS 是发深度学习 · generative models and autoencoders论文最多的会议，2023–2026 年共 1,714 篇，占四个会议总量的 40%。
• 交叉方向里涨得最快的是图像生成：同时属于两个主题的论文从 2023 年的 35 篇增至 2026 年的 150 篇。
• 在「深度学习」的 11 个主题里，它的 2026 年论文数排第 2；同组增长最快的扩散模型是 4.1 倍，深度学习 · generative models and autoencoders是 1.2 倍。

代表论文

按年份和会议均匀挑选，方便快速看到每一届的样貌

• 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

全部深度学习 · generative models and autoencoders论文

共 1,216 篇，第 17 / 25 页

801. NeurIPS 2023Joint Bayesian Inference of Graphical Structure and Parameters with a Single Generative Flow Network
802. NeurIPS 2023Joint Training of Deep Ensembles Fails Due to Learner Collusion
803. NeurIPS 2023JourneyDB: A Benchmark for Generative Image Understanding
804. NeurIPS 2023KAKURENBO: Adaptively Hiding Samples in Deep Neural Network Training
805. NeurIPS 2023Katakomba: Tools and Benchmarks for Data-Driven NetHack
806. NeurIPS 2023Keep Various Trajectories: Promoting Exploration of Ensemble Policies in Continuous Control
807. NeurIPS 2023Keypoint-Augmented Self-Supervised Learning for Medical Image Segmentation with Limited Annotation
808. NeurIPS 2023Kiki or Bouba? Sound Symbolism in Vision-and-Language Models
809. NeurIPS 2023Koopa: Learning Non-stationary Time Series Dynamics with Koopman Predictors
810. NeurIPS 2023Label-Only Model Inversion Attacks via Knowledge Transfer
811. NeurIPS 2023Labeling Neural Representations with Inverse Recognition
812. NeurIPS 2023Large Language Models are Fixated by Red Herrings: Exploring Creative Problem Solving and Einstellung Effect using the Only Connect Wall Dataset
813. NeurIPS 2023Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning
814. NeurIPS 2023LayoutPrompter: Awaken the Design Ability of Large Language Models
815. NeurIPS 2023Learning a 1-layer conditional generative model in total variation
816. NeurIPS 2023Learning and Collusion in Multi-unit Auctions
817. NeurIPS 2023Learning and processing the ordinal information of temporal sequences in recurrent neural circuits
818. NeurIPS 2023Learning Dense Flow Field for Highly-accurate Cross-view Camera Localization
819. NeurIPS 2023Learning Dictionary for Visual Attention
820. NeurIPS 2023Learning Efficient Surrogate Dynamic Models with Graph Spline Networks
821. NeurIPS 2023Learning Energy-based Model via Dual-MCMC Teaching
822. NeurIPS 2023Learning Energy-Based Prior Model with Diffusion-Amortized MCMC
823. NeurIPS 2023Learning Environment-Aware Affordance for 3D Articulated Object Manipulation under Occlusions
824. NeurIPS 2023Learning Exponential Families from Truncated Samples
825. NeurIPS 2023Learning Invariant Representations with a Nonparametric Nadaraya-Watson Head
826. NeurIPS 2023Learning Large-Scale MTP$_2$ Gaussian Graphical Models via Bridge-Block Decomposition
827. NeurIPS 2023Learning Layer-wise Equivariances Automatically using Gradients
828. NeurIPS 2023Learning Mixtures of Gaussians Using the DDPM Objective
829. NeurIPS 2023Learning Modulated Transformation in GANs
830. NeurIPS 2023Learning Multi-agent Behaviors from Distributed and Streaming Demonstrations
831. NeurIPS 2023Learning non-Markovian Decision-Making from State-only Sequences
832. NeurIPS 2023Learning Nonparametric Latent Causal Graphs with Unknown Interventions
833. NeurIPS 2023Learning Sample Difficulty from Pre-trained Models for Reliable Prediction
834. NeurIPS 2023Learning threshold neurons via edge of stability
835. NeurIPS 2023Learning Time-Invariant Representations for Individual Neurons from Population Dynamics
836. NeurIPS 2023Learning to Compress Prompts with Gist Tokens
837. NeurIPS 2023Learning to Configure Separators in Branch-and-Cut
838. NeurIPS 2023Learning To Dive In Branch And Bound
839. NeurIPS 2023Learning to Parameterize Visual Attributes for Open-set Fine-grained Retrieval
840. NeurIPS 2023Learning to Reason and Memorize with Self-Notes
841. NeurIPS 2023Learning to Receive Help: Intervention-Aware Concept Embedding Models
842. NeurIPS 2023Learning to Tokenize for Generative Retrieval
843. NeurIPS 2023Learning Trajectories are Generalization Indicators
844. NeurIPS 2023Learning Transformer Programs
845. NeurIPS 2023Learning Unseen Modality Interaction
846. NeurIPS 2023Learning via Wasserstein-Based High Probability Generalisation Bounds
847. NeurIPS 2023Learning Visual Prior via Generative Pre-Training
848. NeurIPS 2023Learning World Models with Identifiable Factorization
849. NeurIPS 2023LEPARD: Learning Explicit Part Discovery for 3D Articulated Shape Reconstruction
850. NeurIPS 2023Leveraging sparse and shared feature activations for disentangled representation learning

常见问题

2023–2026 年四大会议一共有多少篇深度学习 · generative models and autoencoders论文？

共 4,314 篇，按年份分别是 2023 年 1,216 篇、2024 年 768 篇、2025 年 900 篇、2026 年 1,430 篇。

NeurIPS 2026 有多少篇深度学习 · generative models and autoencoders论文？

NeurIPS 2026 有 349 篇深度学习 · generative models and autoencoders论文，上一届是 240 篇。

ICLR 2026 有多少篇深度学习 · generative models and autoencoders论文？

ICLR 2026 有 303 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。

ICML 2026 有多少篇深度学习 · generative models and autoencoders论文？

ICML 2026 有 604 篇深度学习 · generative models and autoencoders论文，上一届是 275 篇。

CVPR 2026 有多少篇深度学习 · generative models and autoencoders论文？

CVPR 2026 有 174 篇深度学习 · generative models and autoencoders论文，上一届是 110 篇。

哪个会议的深度学习 · generative models and autoencoders论文最多？

NeurIPS，2023–2026 年共 1,714 篇。