算子融合论文趋势 2023–2026

融合优化

统计范围:NeurIPS、ICLR、ICML、CVPR 四个会议,2023–2026 年,共 221 篇被归入该主题的论文。

主要结论

每年论文数

各会议论文数

按年份和会议统计

算子融合论文数,按年份和会议
年份NeurIPSICLRICMLCVPR合计
2023141514851
2024201225966
202525814956
2026149131248

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

全部算子融合论文

共 221 篇,第 3 / 5 页

  1. NeurIPS 2025Scalable Signature Kernel Computations via Local Neumann Series Expansions
  2. NeurIPS 2025SD-KDE: Score-Debiased Kernel Density Estimation
  3. NeurIPS 2025Uncertainty Quantification with the Empirical Neural Tangent Kernel
  4. NeurIPS 2025When Kernels Multiply, Clusters Unify: Fusing Embeddings with the Kronecker Product
  5. CVPR 2024Bi-SSC: Geometric-Semantic Bidirectional Fusion for Camera-based 3D Semantic Scene Completion
  6. CVPR 2024Data-Efficient Multimodal Fusion on a Single GPU
  7. CVPR 2024Embracing Unimodal Aleatoric Uncertainty for Robust Multimodal Fusion
  8. CVPR 2024KPConvX: Modernizing Kernel Point Convolution with Kernel Attention
  9. CVPR 2024PeLK: Parameter-efficient Large Kernel ConvNets with Peripheral Convolution
  10. CVPR 2024Poly Kernel Inception Network for Remote Sensing Detection
  11. CVPR 2024Robust Depth Enhancement via Polarization Prompt Fusion Tuning
  12. CVPR 2024SecondPose: SE(3)-Consistent Dual-Stream Feature Fusion for Category-Level Pose Estimation
  13. CVPR 2024SFOD: Spiking Fusion Object Detector
  14. ICLR 2024An Agnostic View on the Cost of Overfitting in (Kernel) Ridge Regression
  15. ICLR 2024Convolutional Deep Kernel Machines
  16. ICLR 2024Counterfactual Density Estimation using Kernel Stein Discrepancies
  17. ICLR 2024Explaining Kernel Clustering via Decision Trees
  18. ICLR 2024Fusing Models with Complementary Expertise
  19. ICLR 2024lpNTK: Better Generalisation with Less Data via Sample Interaction During Learning
  20. ICLR 2024Posterior Sampling Based on Gradient Flows of the MMD with Negative Distance Kernel
  21. ICLR 2024Scalable Neural Network Kernels
  22. ICLR 2024Smooth ECE: Principled Reliability Diagrams via Kernel Smoothing
  23. ICLR 2024The optimality of kernel classifiers in Sobolev space
  24. ICLR 2024Towards Meta-Pruning via Optimal Transport
  25. ICLR 2024Transformer Fusion with Optimal Transport
  26. ICML 2024Amortized Variational Deep Kernel Learning
  27. ICML 2024Bring Your Own (Non-Robust) Algorithm to Solve Robust MDPs by Estimating The Worst Kernel
  28. ICML 2024Characterizing Overfitting in Kernel Ridgeless Regression Through the Eigenspectrum
  29. ICML 2024Copula-Nested Spectral Kernel Network
  30. ICML 2024Deep Fusion: Efficient Network Training via Pre-trained Initializations
  31. ICML 2024DeepPolar: Inventing Nonlinear Large-Kernel Polar Codes via Deep Learning
  32. ICML 2024Dissecting Multimodality in VideoQA Transformer Models by Impairing Modality Fusion
  33. ICML 2024Generalization in Kernel Regression Under Realistic Assumptions
  34. ICML 2024High-Dimensional Kernel Methods under Covariate Shift: Data-Dependent Implicit Regularization
  35. ICML 2024Is Kernel Prediction More Powerful than Gating in Convolutional Neural Networks?
  36. ICML 2024Kernel Debiased Plug-in Estimation: Simultaneous, Automated Debiasing without Influence Functions for Many Target Parameters
  37. ICML 2024Kernel Semi-Implicit Variational Inference
  38. ICML 2024Kernel-Based Evaluation of Conditional Biological Sequence Models
  39. ICML 2024Mean-field Analysis on Two-layer Neural Networks from a Kernel Perspective
  40. ICML 2024Neural-Kernel Conditional Mean Embeddings
  41. ICML 2024On the Consistency of Kernel Methods with Dependent Observations
  42. ICML 2024Optimal Kernel Quantile Learning with Random Features
  43. ICML 2024Position: Opportunities Exist for Machine Learning in Magnetic Fusion Energy
  44. ICML 2024Predictive Dynamic Fusion
  45. ICML 2024Quasi-Monte Carlo Features for Kernel Approximation
  46. ICML 2024Revealing the Dark Secrets of Extremely Large Kernel ConvNets on Robustness
  47. ICML 2024Reward-Free Kernel-Based Reinforcement Learning
  48. ICML 2024Sampling in Unit Time with Kernel Fisher-Rao Flow
  49. ICML 2024Scalable Multiple Kernel Clustering: Learning Clustering Structure from Expectation
  50. ICML 2024Sequential Kernel Goodness-of-fit Testing

在 Claude、Cursor 里直接问这个趋势

接上 Paperlist MCP 后,写综述、挑方向或准备投稿时,不用离开对话框就能拿到这页的数字:每年各会议的论文数、增长倍数、涨得最快的子方向和代表论文,AI 会按你的问题整理。

可以直接复制这句话问 AI

用 paperlist 查算子融合在 NeurIPS 2023–2026 的论文趋势,哪一年涨得最快?

AI 会调用的工具:get_topic_stats {"topic": "kernel-fusion"}

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常见问题

2023–2026 年四大会议一共有多少篇算子融合论文?
共 221 篇,按年份分别是 2023 年 51 篇、2024 年 66 篇、2025 年 56 篇、2026 年 48 篇。
NeurIPS 2026 有多少篇算子融合论文?
NeurIPS 2026 有 14 篇算子融合论文,上一届是 25 篇。
ICLR 2026 有多少篇算子融合论文?
ICLR 2026 有 9 篇算子融合论文,上一届是 8 篇。
ICML 2026 有多少篇算子融合论文?
ICML 2026 有 13 篇算子融合论文,上一届是 14 篇。
CVPR 2026 有多少篇算子融合论文?
CVPR 2026 有 12 篇算子融合论文,上一届是 9 篇。
哪个会议的算子融合论文最多?
NeurIPS,2023–2026 年共 73 篇。

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