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 13 / 16 页

601. NeurIPS 2024Leveraging Drift to Improve Sample Complexity of Variance Exploding Diffusion Models
602. NeurIPS 2024LG-VQ: Language-Guided Codebook Learning
603. NeurIPS 2024Light Unbalanced Optimal Transport
604. NeurIPS 2024Linguistic Collapse: Neural Collapse in (Large) Language Models
605. NeurIPS 2024LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models
606. NeurIPS 2024LLM Circuit Analyses Are Consistent Across Training and Scale
607. NeurIPS 2024Local Curvature Smoothing with Stein's Identity for Efficient Score Matching
608. NeurIPS 2024Local to Global: Learning Dynamics and Effect of Initialization for Transformers
609. NeurIPS 2024Locating What You Need: Towards Adapting Diffusion Models to OOD Concepts In-the-Wild
610. NeurIPS 2024Looks Too Good To Be True: An Information-Theoretic Analysis of Hallucinations in Generative Restoration Models
611. NeurIPS 2024Lumina-Next : Making Lumina-T2X Stronger and Faster with Next-DiT
612. NeurIPS 2024MambaTalk: Efficient Holistic Gesture Synthesis with Selective State Space Models
613. NeurIPS 2024MassSpecGym: A benchmark for the discovery and identification of molecules
614. NeurIPS 2024Maximum Entropy Inverse Reinforcement Learning of Diffusion Models with Energy-Based Models
615. NeurIPS 2024Mesa-Extrapolation: A Weave Position Encoding Method for Enhanced Extrapolation in LLMs
616. NeurIPS 2024MeshXL: Neural Coordinate Field for Generative 3D Foundation Models
617. NeurIPS 2024Meta 3D AssetGen: Text-to-Mesh Generation with High-Quality Geometry, Texture, and PBR Materials
618. NeurIPS 2024Metric Flow Matching for Smooth Interpolations on the Data Manifold
619. NeurIPS 2024Metric Space Magnitude for Evaluating the Diversity of Latent Representations
620. NeurIPS 2024MIDGArD: Modular Interpretable Diffusion over Graphs for Articulated Designs
621. NeurIPS 2024Mixed Dynamics In Linear Networks: Unifying the Lazy and Active Regimes
622. NeurIPS 2024MoGenTS: Motion Generation based on Spatial-Temporal Joint Modeling
623. NeurIPS 2024Molecule Design by Latent Prompt Transformer
624. NeurIPS 2024MoME: Mixture of Multimodal Experts for Generalist Multimodal Large Language Models
625. NeurIPS 2024MonoMAE: Enhancing Monocular 3D Detection through Depth-Aware Masked Autoencoders
626. NeurIPS 2024MotionCraft: Physics-Based Zero-Shot Video Generation
627. NeurIPS 2024MSAGPT: Neural Prompting Protein Structure Prediction via MSA Generative Pre-Training
628. NeurIPS 2024Multimodal Large Language Models Make Text-to-Image Generative Models Align Better
629. NeurIPS 2024Multistep Distillation of Diffusion Models via Moment Matching
630. NeurIPS 2024MVGamba: Unify 3D Content Generation as State Space Sequence Modeling
631. NeurIPS 2024MVInpainter: Learning Multi-View Consistent Inpainting to Bridge 2D and 3D Editing
632. NeurIPS 2024MVSplat360: Feed-Forward 360 Scene Synthesis from Sparse Views
633. NeurIPS 2024Nature-Inspired Local Propagation
634. NeurIPS 2024Near-Minimax-Optimal Distributional Reinforcement Learning with a Generative Model
635. NeurIPS 2024Nearest Neighbor Speculative Decoding for LLM Generation and Attribution
636. NeurIPS 2024Neural Cover Selection for Image Steganography
637. NeurIPS 2024Neural Flow Diffusion Models: Learnable Forward Process for Improved Diffusion Modelling
638. NeurIPS 2024Neural Pose Representation Learning for Generating and Transferring Non-Rigid Object Poses
639. NeurIPS 2024OmniTokenizer: A Joint Image-Video Tokenizer for Visual Generation
640. NeurIPS 2024On Divergence Measures for Training GFlowNets
641. NeurIPS 2024On Giant's Shoulders: Effortless Weak to Strong by Dynamic Logits Fusion
642. NeurIPS 2024On improved Conditioning Mechanisms and Pre-training Strategies for Diffusion Models
643. NeurIPS 2024On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)
644. NeurIPS 2024On the Complexity of Learning Sparse Functions with Statistical and Gradient Queries
645. NeurIPS 2024On the Identifiability of Hybrid Deep Generative Models: Meta-Learning as a Solution
646. NeurIPS 2024On the Noise Robustness of In-Context Learning for Text Generation
647. NeurIPS 2024One-Shot Safety Alignment for Large Language Models via Optimal Dualization
648. NeurIPS 2024Optimal Flow Matching: Learning Straight Trajectories in Just One Step
649. NeurIPS 2024Optimal Multiclass U-Calibration Error and Beyond
650. NeurIPS 2024Order-Independence Without Fine Tuning

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。