Papers
21 papers found
QiMeng-Kernel: Macro-Thinking Micro-Coding Paradigm for LLM-Based High-Performance GPU Kernel Generation
Xinguo Zhu, Shaohui Peng, Jiaming Guo et al.
Token-Wise Kernels (TWiKers) for Vicinity-Aware Attention in Transformers
Kuangdai Leng, Jia Bi, Samuel Pinilla et al.
SVD-NO: Learning PDE Solution Operators with SVD Integral Kernels
Noam Koren, Ralf J. J. Mackenbach, Ruud J. G. van Sloun et al.
Dual-Kernel Graph Community Contrastive Learning
Xiang Chen, Kun Yue, Wenjie Liu et al.
IDK-S: Incremental Distributional Kernel for Streaming Anomaly Detection
Yang Xu, Yixiao Ma, Kaifeng Zhang et al.
EdgeMTSC: A Lightweight Large-Kernel ConvNet for Multivariate Time Series Classification
Xueyi Zhou, Zhenyu Li, Dong-Kyu Chae
Detecting Unobserved Confounders: A Kernelized Regression Approach
Yikai Chen, Yunxin Mao, Chunyuan Zheng et al.
Enhancing Kernel Power $K$-means: Scalable and Robust Clustering with Random Fourier Features and Possibilistic Method
Yixi Chen, Weixuan Liang, Tianrui Liu et al.
Neural Tangent Kernels Under Stochastic Data Augmentation
Joshua DeOliveira, Sajal Chakroborty, Walter Gerych et al.
Adaptive Hyperbolic Kernels: Modulated Embedding in de Branges-Rovnyak Spaces
Leping Si, Meimei Yang, Hui Xue et al.
Kernelized Edge Attention: Addressing Semantic Attention Blurring in Temporal Graph Neural Networks
Govind Waghmare, Srini Rohan Gujulla Leel, Nikhil Tumbde et al.
AdaFuse: Accelerating Dynamic Adapter Inference via Token-Level Pre-Gating and Fused Kernel Optimization
Qiyang Li, Rui Kong, Yuchen Li et al.
DETONATE – A Benchmark for Text-to-Image Alignment and Kernelized Direct Preference Optimization
Renjith Prasad Kaippilly Mana, Abhilekh Borah, Hasnat Md Abdullah et al.
Geometrically Inspired Kernel Machines for Collaborative Learning Beyond Gradient Descent (Abstract Reprint)
Mohit Kumar, Alexander Valentinitsch, Magdalena Fuchs et al.
CuBridge: An LLM-Based Framework for Understanding and Reconstructing High-Performance Attention Kernels
Xing Ma, Yangjie Zhou, Wu Sun et al.
Taming System Complexity: Demystifying Software Engineering Agents in Diagnosing Linux Kernel Faults
Zhenhao Zhou, Zhuochen Huang, Yike He et al.
Deep Kernel Fusion for Transformers
Zixi Zhang, Zhiwen Mo, Yiren Zhao et al.
Taming Extreme Tokens: Covariance-Aware GRPO with Gaussian-Kernel Advantage Reweighting
Cheng Wang, Qin Liu, Wenxuan Zhou et al.
Bridging Kernel Drivers and Virtual Device Models with LLM-Powered Automation
Mingyu Wang, Bin Yu, Wenjian Lu et al.
A comprehensive benchmark of graph neural networks, graph kernels, and classical machine learning approaches on rs-fMRI brain graphs
Razan Mhanna, Sophie Achard, Alexander Petersen et al.
A Martingale Kernel Two-Sample Test
Anirban Chatterjee, Aaditya Ramdas