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 4,314 篇，第 70 / 87 页

3451. ICML 2023On the Convergence Rate of Gaussianization with Random Rotations
3452. ICML 2023On the Functional Similarity of Robust and Non-Robust Neural Representations
3453. ICML 2023On the Power of Pre-training for Generalization in RL: Provable Benefits and Hardness
3454. ICML 2023On the Relationship Between Explanation and Prediction: A Causal View
3455. ICML 2023Optimizing NOTEARS Objectives via Topological Swaps
3456. ICML 2023Oracles & Followers: Stackelberg Equilibria in Deep Multi-Agent Reinforcement Learning
3457. ICML 2023Orthogonality-Enforced Latent Space in Autoencoders: An Approach to Learning Disentangled Representations
3458. ICML 2023Out-of-Distribution Generalization of Federated Learning via Implicit Invariant Relationships
3459. ICML 2023Overcoming Simplicity Bias in Deep Networks using a Feature Sieve
3460. ICML 2023PAC-Bayesian Generalization Bounds for Adversarial Generative Models
3461. ICML 2023Paging with Succinct Predictions
3462. ICML 2023Pareto Manifold Learning: Tackling multiple tasks via ensembles of single-task models
3463. ICML 2023Performative Reinforcement Learning
3464. ICML 2023Personalized Federated Learning with Inferred Collaboration Graphs
3465. ICML 2023Personalized Subgraph Federated Learning
3466. ICML 2023PFGM++: Unlocking the Potential of Physics-Inspired Generative Models
3467. ICML 2023Poisoning Generative Replay in Continual Learning to Promote Forgetting
3468. ICML 2023Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach
3469. ICML 2023Policy Mirror Ascent for Efficient and Independent Learning in Mean Field Games
3470. ICML 2023Policy Regularization with Dataset Constraint for Offline Reinforcement Learning
3471. ICML 2023Probabilistic Contrastive Learning Recovers the Correct Aleatoric Uncertainty of Ambiguous Inputs
3472. ICML 2023Prometheus: Taming Sample and Communication Complexities in Constrained Decentralized Stochastic Bilevel Learning
3473. ICML 2023Proper Losses for Discrete Generative Models
3474. ICML 2023Provably Learning Object-Centric Representations
3475. ICML 2023Q-Flow: Generative Modeling for Differential Equations of Open Quantum Dynamics with Normalizing Flows
3476. ICML 2023Q-learning Decision Transformer: Leveraging Dynamic Programming for Conditional Sequence Modelling in Offline RL
3477. ICML 2023Quantile Credit Assignment
3478. ICML 2023Quantitative Universal Approximation Bounds for Deep Belief Networks
3479. ICML 2023Recasting Self-Attention with Holographic Reduced Representations
3480. ICML 2023Refining Generative Process with Discriminator Guidance in Score-based Diffusion Models
3481. ICML 2023Reflected Diffusion Models
3482. ICML 2023Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice
3483. ICML 2023Regularizing Towards Soft Equivariance Under Mixed Symmetries
3484. ICML 2023Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition
3485. ICML 2023Restoration based Generative Models
3486. ICML 2023Revisiting Discriminative vs. Generative Classifiers: Theory and Implications
3487. ICML 2023Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees
3488. ICML 2023Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature
3489. ICML 2023Revisiting Structured Variational Autoencoders
3490. ICML 2023Robust and private stochastic linear bandits
3491. ICML 2023Robust Collaborative Learning with Linear Gradient Overhead
3492. ICML 2023Robust Consensus in Ranking Data Analysis: Definitions, Properties and Computational Issues
3493. ICML 2023Robust Non-Linear Feedback Coding via Power-Constrained Deep Learning
3494. ICML 2023Sample Complexity Bounds for Learning High-dimensional Simplices in Noisy Regimes
3495. ICML 2023Scaling Laws for Generative Mixed-Modal Language Models
3496. ICML 2023SGD with Large Step Sizes Learns Sparse Features
3497. ICML 2023Shape-Guided Dual-Memory Learning for 3D Anomaly Detection
3498. ICML 2023Solving High-Dimensional PDEs with Latent Spectral Models
3499. ICML 2023SparseGPT: Massive Language Models Can be Accurately Pruned in One-Shot
3500. ICML 2023Special Properties of Gradient Descent with Large Learning Rates

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。