177 citations · 189 across the 18 of their papers we have counts for
21 papers
ROTE: Benchmarking Neural Memorization on Complexity-Controlled Symbolic Sequences
Xinye Chen, Stefan Güttel, Mohammad Mozaffari
We introduce ROTE (RollOut Testing of Exact memorization), a benchmarking protocol for evaluating symbolic memorization of neural architectures. We study memorization and the exten…
Integral chemical reaction neural networks
Abraham Reyes-Velázquez, Stefan Güttel
Discovering the structure and kinetics of chemical reaction networks (CRNs) from time-series concentration data is a fundamental challenge in chemical kinetics, with existing appro…
Uniform-in-time rational approximation of the matrix exponential with real poles
Stefan Güttel, Shuai Shao
We propose two new approaches for constructing families of rational functions with shared real poles that nearly uniformly approximate the functions for and $…
Sketch-and-Restart: Randomized Sketching in Quadrature-Based Restarting for Matrix Functions
Stefan Güttel, Jingyu Liu, Lauri Nyman
We develop a sketch-and-restart framework for computing the action of a matrix function on a vector, , where is large, sparse, and non-Hermitian. The framework combines…
Scalable parallel 3-D TEM inversion via rational approximation of the matrix exponential
Ralph-Uwe Börner, Stefan Güttel, Thomas Günther
We present a novel parallel implementation for large-scale three-dimensional electromagnetic inversion based on a Gauss-Newton framework combined with a rational near-best approxim…
Concentrated real-pole uniform-in-time approximation of the matrix exponential
Stefan Güttel, Shuai Shao
We propose an asympotically optimal choice of shared concentrated real poles of a family of rational approximants of time-dependent exponential functions for …
fastGMRES: Robust randomized GMRES via flexible GMRES
Stefan Güttel, John W. Pearson
We propose a practical randomized algorithm for solving large sparse systems of linear equations. The algorithm, termed fastGMRES, uses flexible GMRES as an outer wrapper for sketc…
A Sherman--Morrison--Woodbury approach to solving least squares problems with low-rank updates
Stefan Güttel, Yuji Nakatsukasa, Marcus Webb +1
We present a simple formula to update the pseudoinverse of a full-rank rectangular matrix that undergoes a low-rank modification, and demonstrate its utility for solving least squa…
GMRES with randomized sketching and deflated restarting
Liam Burke, Stefan Güttel, Kirk M. Soodhalter
We present a new Krylov subspace recycling method for solving a linear system of equations, or a sequence of slowly changing linear systems. Our approach is to reduce the computati…
Krylov Subspace Recycling With Randomized Sketching For Matrix Functions
Liam Burke, Stefan Güttel
A Krylov subspace recycling method for the efficient evaluation of a sequence of matrix functions acting on a set of vectors is developed. The method improves over the recycling me…
A sketch-and-select Arnoldi process
Stefan Güttel, Igor Simunec
A sketch-and-select Arnoldi process to generate a well-conditioned basis of a Krylov space at low cost is proposed. At each iteration the procedure utilizes randomized sketching to…
Fast and exact fixed-radius neighbor search based on sorting
Xinye Chen, Stefan Güttel
Fixed-radius near neighbor search is a fundamental data operation that retrieves all data points within a user-specified distance to a query point. There are efficient algorithms t…
Randomized sketching of nonlinear eigenvalue problems
Stefan Güttel, Daniel Kressner, Bart Vandereycken
Rational approximation is a powerful tool to obtain accurate surrogates for nonlinear functions that are easy to evaluate and linearize. The interpolatory adaptive Antoulas--Anders…
Randomized sketching for Krylov approximations of large-scale matrix functions
Stefan Güttel, Marcel Schweitzer
The computation of f(A)b, the action of a matrix function on a vector, is a task arising in many areas of scientific computing. In many applications, the matrix A is sparse but so…
Fast and explainable clustering based on sorting
Xinye Chen, Stefan Güttel
We introduce a fast and explainable clustering method called CLASSIX. It consists of two phases, namely a greedy aggregation phase of the sorted data into groups of nearby data poi…
Machine Learning-Based Soft Sensors for Vacuum Distillation Unit
Kamil Oster, Stefan Güttel, Lu Chen +2
Product quality assessment in the petroleum processing industry can be difficult and time-consuming, e.g. due to a manual collection of liquid samples from the plant and subsequent…
Calculating elements of matrix functions using divided differences
Lev Barash, Stefan Güttel, Itay Hen
We introduce a method for calculating individual elements of matrix functions. Our technique makes use of a novel series expansion for the action of matrix functions on basis vecto…
A comparison of LSTM and GRU networks for learning symbolic sequences
Roberto Cahuantzi, Xinye Chen, Stefan Güttel
We explore the architecture of recurrent neural networks (RNNs) by studying the complexity of string sequences it is able to memorize. Symbolic sequences of different complexity ar…
Conversions between barycentric, RKFUN, and Newton representations of rational interpolants
Steven Elsworth, Stefan Güttel
We derive explicit formulas for converting between rational interpolants in barycentric, rational Krylov (RKFUN), and Newton form. We show applications of these conversions when wo…
Near-optimal perfectly matched layers for indefinite Helmholtz problems
Vladimir Druskin, Stefan Güttel, Leonid Knizhnerman
A new construction of an absorbing boundary condition for indefinite Helmholtz problems on unbounded domains is presented. This construction is based on a near-best uniform rationa…
Zolotarev Quadrature Rules and Load Balancing for the FEAST Eigensolver
Stefan Guettel, Eric Polizzi, Ping Tak Peter Tang +1
The FEAST method for solving large sparse eigenproblems is equivalent to subspace iteration with an approximate spectral projector and implicit orthogonalization. This relation all…