Publications related to A kernel compression scheme for fractional differential equations

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Jan Sickmann Hesthaven, Mariella Kast, Mengwu Guo

We propose a non-intrusive reduced basis (RB) method for parametrized nonlinear partial differential equations (PDEs) that leverages models of different accuracy. From a collection of low-fidelity (LF) snapshots, parameter locations are extracted for the e ...

ELSEVIER SCIENCE SA2020

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

Michele Ceriotti, Michael John Willatt

We briefly summarize the kernel regression approach, as used recently in materials modelling, to fitting functions, particularly potential energy surfaces, and highlight how the linear algebra framework can be used to both predict and train from linear fun ...

Springer International Publishing2020

A local discontinuous Galerkin gradient discretization method for linear and quasilinear elliptic equations

Assyr Abdulle, Giacomo Rosilho De Souza

A local weighted discontinuous Galerkin gradient discretization method for solving elliptic equations is introduced. The local scheme is based on a coarse grid and successively improves the solution solving a sequence of local elliptic problems in high gra ...

EDP SCIENCES S A2019

RBF Based CWENO Method

Jan Sickmann Hesthaven, Fabian Mönkeberg

Solving hyperbolic conservation laws on general grids can be important to reduce the computational complexity and increase accuracy in many applications. However, the use of non-uniform grids can introduce challenges when using high-order methods. We propo ...

2018

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Andy Roulin

Modern data-center network operating systems rely on proprietary user-space daemons wrapping SDKs from switch vendors. Linux-based variants of these operating systems have benefited from increasing and simplified dataplane offloading support in recent year ...

2018

Cooperative data exchange based on MDS codes

Michael Christoph Gastpar, Su Li

The coded cooperative data exchange problem is studied for the fully connected network. In this problem, each node initially only possesses a subset of the K packets making up the file. Nodes make broadcast transmissions that are received by all other node ...

2017

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Volkan Cevher, Jonathan Mark Scarlett, Ilija Bogunovic

In this paper, we consider the problem of sequentially optimizing a black-box function

f

based on noisy samples and bandit feedback. We assume that

f

is smooth in the sense of having a bounded norm in some reproducing kernel Hilbert space (RKHS), yield ...

2017

Autonomous Learning of Internal Dynamic Models for Reaching Tasks

Auke Ijspeert, Tadej Petric

The paper addresses the problem of learning internal task-specific dynamic models for a reaching task. Using task-specific dynamic models is crucial for achieving both high tracking accuracy and compliant behaviour, which improves safety concerns while wor ...

Springer-Verlag Berlin2016

Guaranteeing Input Tracking For Constrained Systems: Theory and Application to Demand Response

Colin Neil Jones, Tomasz Tadeusz Gorecki, Georgios Stathopoulos, Altug Bitlislioglu

A method for certifying exact input trackability for constrained discrete time linear systems is introduced in this paper. A signal is assumed to be drawn from a reference set and the system must track this signal with a linear combination of its inputs. U ...

2015

Cross-correlated relaxation measurements under adiabatic sweeps: determination of local order in proteins

Geoffrey Bodenhausen, Nicola Salvi, Pavel Kaderavek, Fabien Ferrage

Adiabatically swept pulses were originally designed for the purpose of broadband spin inversion. Later, unexpected advantages of their utilization were also found in other applications, such as refocusing to excite spin echoes, studies of chemical exchange ...

Springer Verlag2015

A kernel compression scheme for fractional differential equations

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A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

A local discontinuous Galerkin gradient discretization method for linear and quasilinear elliptic equations

RBF Based CWENO Method

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Cooperative data exchange based on MDS codes

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Autonomous Learning of Internal Dynamic Models for Reaching Tasks

Guaranteeing Input Tracking For Constrained Systems: Theory and Application to Demand Response

Cross-correlated relaxation measurements under adiabatic sweeps: determination of local order in proteins

RBF Based CWENO Method

Machine-Learning of Atomic-Scale Properties Based on Physical Principles

A local discontinuous Galerkin gradient discretization method for linear and quasilinear elliptic equations

Cooperative data exchange based on MDS codes

Guaranteeing Input Tracking For Constrained Systems: Theory and Application to Demand Response

A non-intrusive multifidelity method for the reduced order modeling of nonlinear problems

Autonomous Learning of Internal Dynamic Models for Reaching Tasks

Advancing the State of Network Switch ASIC Offloading in the Linux Kernel

Lower Bounds on Regret for Noisy Gaussian Process Bandit Optimization

Cross-correlated relaxation measurements under adiabatic sweeps: determination of local order in proteins