Anders Szepessy

About Anders Szepessy

Anders Szepessy, With an exceptional h-index of 23 and a recent h-index of 11 (since 2020), a distinguished researcher at Kungliga Tekniska högskolan,

His recent articles reflect a diverse array of research interests and contributions to the field:

Smaller generalization error derived for a deep residual neural network compared with shallow networks

Path integral molecular dynamics approximations of quantum canonical observables

Canonical mean-field molecular dynamics derived from quantum mechanics

Computational Results on Canonical Mean-field Molecular Dynamics Approximation of Quantum Mechanics

COMPUTATIONAL ALGORITHMS FOR CANONICAL ENSEMBLE OBSERVABLES

Smaller generalization error derived for deep compared to shallow residual neural networks

Adaptive random Fourier features with Metropolis sampling

Anders Szepessy Information

University

Position

Stockholm

Citations(all)

2954

Citations(since 2020)

392

Cited By

2818

hIndex(all)

23

hIndex(since 2020)

11

i10Index(all)

43

i10Index(since 2020)

16

Email

University Profile Page

Google Scholar

Top articles of Anders Szepessy

Title

Journal

Author(s)

Publication Date

Smaller generalization error derived for a deep residual neural network compared with shallow networks

IMA Journal of Numerical Analysis

Aku Kammonen

Jonas Kiessling

Petr Plecháč

Mattias Sandberg

Anders Szepessy

...

2023/9

Path integral molecular dynamics approximations of quantum canonical observables

arXiv preprint arXiv:2311.17333

Xin Huang

Petr Plechac

Mattias Sandberg

Anders Szepessy

2023/11/29

Canonical mean-field molecular dynamics derived from quantum mechanics

ESAIM: Mathematical Modelling and Numerical Analysis

Xin Huang

Petr Plecháč

Mattias Sandberg

Anders Szepessy

2022/11/1

Computational Results on Canonical Mean-field Molecular Dynamics Approximation of Quantum Mechanics

Xin Huang

2022/5/22

COMPUTATIONAL ALGORITHMS FOR CANONICAL ENSEMBLE OBSERVABLES

Aku Kammonen

Petr Plecháč

Mattias Sandberg

Anders Szepessy

2020

Smaller generalization error derived for deep compared to shallow residual neural networks

arXiv preprint arXiv:2010.01887

Aku Kammonen

Jonas Kiessling

Petr Plechác

Mattias Sandberg

Anders Szepessy

...

2020/10/5

Adaptive random Fourier features with Metropolis sampling

arXiv preprint arXiv:2007.10683

Aku Kammonen

Jonas Kiessling

Petr Plecháč

Mattias Sandberg

Anders Szepessy

2020/7/21

See List of Professors in Anders Szepessy University(Kungliga Tekniska högskolan)