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 768 篇，第 9 / 16 页

401. ICML 2024Stability and Generalization of Stochastic Compositional Gradient Descent Algorithms
402. ICML 2024Stacking Deep Set Networks and Pooling by Quantiles
403. ICML 2024Statistically Optimal Generative Modeling with Maximum Deviation from the Empirical Distribution
404. ICML 2024Stochastic Interpolants with Data-Dependent Couplings
405. ICML 2024StrWAEs to Invariant Representations
406. ICML 2024Switched Flow Matching: Eliminating Singularities via Switching ODEs
407. ICML 2024The Emergence of Reproducibility and Consistency in Diffusion Models
408. ICML 2024The Good, The Bad, and Why: Unveiling Emotions in Generative AI
409. ICML 2024The Linear Representation Hypothesis and the Geometry of Large Language Models
410. ICML 2024The Stronger the Diffusion Model, the Easier the Backdoor: Data Poisoning to Induce Copyright BreachesWithout Adjusting Finetuning Pipeline
411. ICML 2024Timer: Generative Pre-trained Transformers Are Large Time Series Models
412. ICML 2024Topological Neural Networks go Persistent, Equivariant, and Continuous
413. ICML 2024Towards AutoAI: Optimizing a Machine Learning System with Black-box and Differentiable Components
414. ICML 2024Towards Neural Architecture Search through Hierarchical Generative Modeling
415. ICML 2024Towards Scalable and Versatile Weight Space Learning
416. ICML 2024Towards Theoretical Understandings of Self-Consuming Generative Models
417. ICML 2024Transformers, parallel computation, and logarithmic depth
418. ICML 2024Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues
419. ICML 2024Why do Variational Autoencoders Really Promote Disentanglement?
420. NeurIPS 2024[Re] GNNInterpreter: A probabilistic generative model-level explanation for Graph Neural Networks
421. NeurIPS 20244Diffusion: Multi-view Video Diffusion Model for 4D Generation
422. NeurIPS 20244M-21: An Any-to-Any Vision Model for Tens of Tasks and Modalities
423. NeurIPS 20244Real: Towards Photorealistic 4D Scene Generation via Video Diffusion Models
424. NeurIPS 2024A Cat Is A Cat (Not A Dog!): Unraveling Information Mix-ups in Text-to-Image Encoders through Causal Analysis and Embedding Optimization
425. NeurIPS 2024A Closer Look at AUROC and AUPRC under Class Imbalance
426. NeurIPS 2024A Functional Extension of Semi-Structured Networks
427. NeurIPS 2024A Generative Model of Symmetry Transformations
428. NeurIPS 2024A Geometric View of Data Complexity: Efficient Local Intrinsic Dimension Estimation with Diffusion Models
429. NeurIPS 2024A scalable generative model for dynamical system reconstruction from neuroimaging data
430. NeurIPS 2024A Simple and Optimal Approach for Universal Online Learning with Gradient Variations
431. NeurIPS 2024A Theoretical Understanding of Self-Correction through In-context Alignment
432. NeurIPS 2024A versatile informative diffusion model for single-cell ATAC-seq data generation and analysis
433. NeurIPS 2024Absorb & Escape: Overcoming Single Model Limitations in Generating Heterogeneous Genomic Sequences
434. NeurIPS 2024ACES: Generating a Diversity of Challenging Programming Puzzles with Autotelic Generative Models
435. NeurIPS 2024Advancing Tool-Augmented Large Language Models: Integrating Insights from Errors in Inference Trees
436. NeurIPS 2024Adversarial Representation Engineering: A General Model Editing Framework for Large Language Models
437. NeurIPS 2024Adversarial Schrödinger Bridge Matching
438. NeurIPS 2024AFBench: A Large-scale Benchmark for Airfoil Design
439. NeurIPS 2024AirSketch: Generative Motion to Sketch
440. NeurIPS 2024Aligning Diffusion Models by Optimizing Human Utility
441. NeurIPS 2024An Equivalence Between Static and Dynamic Regret Minimization
442. NeurIPS 2024An Image is Worth 32 Tokens for Reconstruction and Generation
443. NeurIPS 2024Animate3D: Animating Any 3D Model with Multi-view Video Diffusion
444. NeurIPS 2024Applying Guidance in a Limited Interval Improves Sample and Distribution Quality in Diffusion Models
445. NeurIPS 2024Architect: Generating Vivid and Interactive 3D Scenes with Hierarchical 2D Inpainting
446. NeurIPS 2024Are More LLM Calls All You Need? Towards the Scaling Properties of Compound AI Systems
447. NeurIPS 2024ArkVale: Efficient Generative LLM Inference with Recallable Key-Value Eviction
448. NeurIPS 2024Atlas3D: Physically Constrained Self-Supporting Text-to-3D for Simulation and Fabrication
449. NeurIPS 2024Autoregressive Image Generation without Vector Quantization
450. NeurIPS 2024Bandit-Feedback Online Multiclass Classification: Variants and Tradeoffs

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。