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 1,304 篇，第 16 / 27 页

751. ICML 2025Learning Latent Graph Structures and their Uncertainty
752. ICML 2025Learning Monotonic Probabilities with a Generative Cost Model
753. ICML 2025Learning Multi-Level Features with Matryoshka Sparse Autoencoders
754. ICML 2025Learning Robust Neural Processes with Risk-Averse Stochastic Optimization
755. ICML 2025Learning to Match Unpaired Data with Minimum Entropy Coupling
756. ICML 2025Learning to Quantize for Training Vector-Quantized Networks
757. ICML 2025Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
758. ICML 2025LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
759. ICML 2025LOB-Bench: Benchmarking Generative AI for Finance - an Application to Limit Order Book Data
760. ICML 2025Low-Rank Adapting Models for Sparse Autoencoders
761. ICML 2025Masked Autoencoders Are Effective Tokenizers for Diffusion Models
762. ICML 2025Masked Generative Nested Transformers with Decode Time Scaling
763. ICML 2025MDDM: Practical Message-Driven Generative Image Steganography Based on Diffusion Models
764. ICML 2025Measuring Diversity: Axioms and Challenges
765. ICML 2025Mechanisms of Projective Composition of Diffusion Models
766. ICML 2025MGD$^3$ : Mode-Guided Dataset Distillation using Diffusion Models
767. ICML 2025MimicMotion: High-Quality Human Motion Video Generation with Confidence-aware Pose Guidance
768. ICML 2025MissScore: High-Order Score Estimation in the Presence of Missing Data
769. ICML 2025MITIGATING OVER-EXPLORATION IN LATENT SPACE OPTIMIZATION USING LES
770. ICML 2025MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
771. ICML 2025Modulated Diffusion: Accelerating Generative Modeling with Modulated Quantization
772. ICML 2025Morse: Dual-Sampling for Lossless Acceleration of Diffusion Models
773. ICML 2025Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion
774. ICML 2025Multilayer Matrix Factorization via Dimension-Reducing Diffusion Variational Inference
775. ICML 2025MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
776. ICML 2025Near-Optimal Sample Complexity for MDPs via Anchoring
777. ICML 2025Neighbour-Driven Gaussian Process Variational Autoencoders for Scalable Structured Latent Modelling
778. ICML 2025NETS: A Non-equilibrium Transport Sampler
779. ICML 2025NMA-tune: Generating Highly Designable and Dynamics Aware Protein Backbones
780. ICML 2025Noise Conditional Variational Score Distillation
781. ICML 2025Normalizing Flows are Capable Generative Models
782. ICML 2025NTPP: Generative Speech Language Modeling for Dual-Channel Spoken Dialogue via Next-Token-Pair Prediction
783. ICML 2025OmiAD: One-Step Adaptive Masked Diffusion Model for Multi-class Anomaly Detection via Adversarial Distillation
784. ICML 2025On Expressive Power of Looped Transformers: Theoretical Analysis and Enhancement via Timestep Encoding
785. ICML 2025On the Guidance of Flow Matching
786. ICML 2025Outsourced Diffusion Sampling: Efficient Posterior Inference in Latent Spaces of Generative Models
787. ICML 2025Overcoming Spurious Solutions in Semi-Dual Neural Optimal Transport: A Smoothing Approach for Learning the Optimal Transport Plan
788. ICML 2025Perceptually Constrained Precipitation Nowcasting Model
789. ICML 2025Physics-Informed Generative Modeling of Wireless Channels
790. ICML 2025PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
791. ICML 2025PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
792. ICML 2025Position: All Current Generative Fidelity and Diversity Metrics are Flawed
793. ICML 2025Position: Challenges and Future Directions of Data-Centric AI Alignment
794. ICML 2025Position: Evaluating Generative AI Systems Is a Social Science Measurement Challenge
795. ICML 2025Position: Future Research and Challenges Remain Towards AI for Software Engineering
796. ICML 2025Position: Generative AI Regulation Can Learn from Social Media Regulation
797. ICML 2025Position: The AI Conference Peer Review Crisis Demands Author Feedback and Reviewer Rewards
798. ICML 2025Position: The Artificial Intelligence and Machine Learning Community Should Adopt a More Transparent and Regulated Peer Review Process
799. ICML 2025Position: You Can't Manufacture a NeRF
800. ICML 2025Positional Attention: Expressivity and Learnability of Algorithmic Computation

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。