90 citations · 116 across the 16 of their papers we have counts for
3 papers · 2 filters
ConDiff: A Challenging Dataset for Neural Solvers of Partial Differential Equations
Vladislav Trifonov, Alexander Rudikov, Oleg Iliev +3
We present ConDiff, a novel dataset for scientific machine learning. ConDiff focuses on the parametric diffusion equation with space dependent coefficients, a fundamental problem i…
Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers
Vladislav Trifonov, Alexander Rudikov, Oleg Iliev +3
Large linear systems are ubiquitous in modern computational science and engineering. The main recipe for solving them is the use of Krylov subspace iterative methods with well-desi…
Quantization of Large Language Models with an Overdetermined Basis
Daniil Merkulov, Daria Cherniuk, Alexander Rudikov +4
In this paper, we introduce an algorithm for data quantization based on the principles of Kashin representation. This approach hinges on decomposing any given vector, matrix, or te…