Thomas Gärtner

About Thomas Gärtner

Thomas Gärtner, With an exceptional h-index of 27 and a recent h-index of 19 (since 2020), a distinguished researcher at Technische Universität Wien, specializes in the field of Machine Learning, Data Mining.

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

Reaction Rebalancing: A Novel Approach to Curating Reaction Databases

Expressivity-preserving GNN simulation

Maximally expressive GNNs for outerplanar graphs

Comparison of Bayesian Networks, G-estimation and linear models to estimate causal treatment effects in aggregated N-of-1 trials with carry-over effects

Expectation-complete graph representations with homomorphisms

Can stochastic weight averaging improve generalization in private learning?

Improving Expert Specialization in Mixture of Experts

No PAIN no Gain: More Expressive GNNs with Paths

Thomas Gärtner Information

University

Position

(Technical University of Vienna)

Citations(all)

5818

Citations(since 2020)

1658

Cited By

4889

hIndex(all)

27

hIndex(since 2020)

19

i10Index(all)

49

i10Index(since 2020)

27

Email

University Profile Page

Google Scholar

Thomas Gärtner Skills & Research Interests

Machine Learning

Data Mining

Top articles of Thomas Gärtner

Reaction Rebalancing: A Novel Approach to Curating Reaction Databases

2024/3/22

Expressivity-preserving GNN simulation

Advances in Neural Information Processing Systems

2023

Maximilian Thiessen
Maximilian Thiessen

H-Index: 1

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Maximally expressive GNNs for outerplanar graphs

2023/12/21

Comparison of Bayesian Networks, G-estimation and linear models to estimate causal treatment effects in aggregated N-of-1 trials with carry-over effects

BMC Medical Research Methodology

2023/8/21

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Expectation-complete graph representations with homomorphisms

2023

Can stochastic weight averaging improve generalization in private learning?

2023/4/16

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Improving Expert Specialization in Mixture of Experts

arXiv preprint arXiv:2302.14703

2023/2/28

No PAIN no Gain: More Expressive GNNs with Paths

2023

Krein support vector machine classification of antimicrobial peptides

Digital discovery

2023

Alex Brown
Alex Brown

H-Index: 20

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Expectation complete graph representations using graph homomorphisms

2022/11/22

Weisfeiler and Leman return with graph transformations

2022/9/19

Maximilian Thiessen
Maximilian Thiessen

H-Index: 1

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Online learning of convex sets on graphs

2022

Maximilian Thiessen
Maximilian Thiessen

H-Index: 1

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Reducing learning on cell complexes to graphs

2022/3/2

Maximilian Thiessen
Maximilian Thiessen

H-Index: 1

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Controllable Network Data Balancing with GANs

2021/12/8

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Tanja Zseby
Tanja Zseby

H-Index: 14

Active learning of convex halfspaces on graphs

Advances in Neural Information Processing Systems

2021/12/6

Maximilian Thiessen
Maximilian Thiessen

H-Index: 1

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Kernel methods for predicting yields of chemical reactions

2021/10/26

Disentangled Representations using Trained Models

2021/10/6

Active learning on graphs with geodesically convex classes

2020

Maximilian Thiessen
Maximilian Thiessen

H-Index: 1

Thomas Gärtner
Thomas Gärtner

H-Index: 17

Machine Learning for Chemical Synthesis

2020/7/15

Interactive Machine Learning with Structured Data.

2020

Thomas Gärtner
Thomas Gärtner

H-Index: 17

See List of Professors in Thomas Gärtner University(Technische Universität Wien)

Co-Authors

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