12 papers
Automated Numerical Stability Analysis of Deep Learning Operators
Xinye Chen
Finite-precision arithmetic unavoidably introduces numerical approximation errors. Numerical computations may use insufficient precision or an improper formulation, which leads to…
Estimating Condition Number with Graph Neural Networks
Erin Carson, Xinye Chen
In this paper, we propose a fast method for estimating the condition number of sparse matrices using graph neural networks (GNNs). For efficient deployment of GNNs, we introduce a…
Floating-point autotuning with customized precisions
Xinye Chen, Thibault Hilaire, Fabienne Jézéquel
Reduced-precision arithmetic offers significant opportunities to improve performance, memory usage, and energy efficiency in numerical applications, provided that numerical accurac…
Computing k-means in mixed precision
Erin Carson, Xinye Chen, Xiaobo Liu
Motivated by the increasing availability of low- and mixed-precision arithmetic on modern hardware, we develop mixed-precision variants of Lloyd's algorithm for k-means clustering.…
Parallel Two-Stage Approach for Joint Symbolic Approximation of Time Series
Xinye Chen
As time-series applications grow larger, there is increasing demand for symbolic representations that are compact, accurate, and scalable across many signals and computing resource…
Using Laplace Transform To Optimize the Hallucination of Generation Models
Cheng Kang, Xinye Chen, Daniel Novak +1
To explore the feasibility of avoiding the confident error (or hallucination) of generation models (GMs), we formalise the system of GMs as a class of stochastic dynamical systems…