Michael Scherbela

Postdoc, Universität Vienna

Joined

May 2022

Names

Michael Scherbela (Preferred)

Emails

****@univie.ac.at (Confirmed)

****@gmail.com (Confirmed)

Personal Links

Google Scholar

DBLP

ORCID

Career & Education History

Postdoc

Universität Vienna (univie.ac.at)

2024 – Present

PhD student

Universität Vienna (univie.ac.at)

2020 – 2024

MS student

Institute of Solid State Physics - Graz University of Technology (if.tugraz.at)

2016 – 2017

Advisors, Relations & Conflicts

Coauthor

Nicholas Gao

2024 – Present

PhD Advisor

Philipp Grohs

2020 – Present

Coauthor

Leon Gerard

2020 – 2024

Coauthor

Oliver Hofmann

2016 – 2017

Expertise

Computational chemistry

Present

Material Science

Present

Neural Network Wavefunctions

Present

Publications

Variational Monte Carlo on a Budget — Fine-tuning pre-trained Neural Wavefunctions
Michael Scherbela, Leon Gerard, Philipp Grohs
- NeurIPS 2023 poster
- Readers: Everyone
Towards a Foundation Model for Neural Network Wavefunctions
Michael Scherbela, Leon Gerard, Philipp Grohs
- 2023 (modified: 18 Apr 2023)
- CoRR 2023
- Readers: Everyone
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?
Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs
- Published: 31 Oct 2022, Last Modified: 08 Feb 2026
- NeurIPS 2022 Accept
- Readers: Everyone
Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?
Leon Gerard, Michael Scherbela, Philipp Marquetand, Philipp Grohs
- Published: 01 Jan 2022, Last Modified: 15 May 2023
- NeurIPS 2022
- Readers: Everyone
Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks
Michael Scherbela, Rafael Reisenhofer, Leon Gerard, Philipp Marquetand, Philipp Grohs
- 2021 (modified: 18 Apr 2023)
- CoRR 2021
- Readers: Everyone
SAMPLE: Surface structure search enabled by coarse graining and statistical learning
Lukas Hörmann, Andreas Jeindl, Alexander T. Egger, Michael Scherbela, Oliver T. Hofmann
- Published: 01 Jan 2019, Last Modified: 15 May 2023
- Comput. Phys. Commun. 2019
- Readers: Everyone

Michael Scherbela

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Variational Monte Carlo on a Budget — Fine-tuning pre-trained Neural Wavefunctions

Towards a Foundation Model for Neural Network Wavefunctions

Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?

Gold-standard solutions to the Schrödinger equation using deep learning: How much physics do we need?

Solving the electronic Schrödinger equation for multiple nuclear geometries with weight-sharing deep neural networks

SAMPLE: Surface structure search enabled by coarse graining and statistical learning

Co-Authors