Philipp Renz

About Philipp Renz

Philipp Renz, With an exceptional h-index of 5 and a recent h-index of 5 (since 2020), a distinguished researcher at Johannes Kepler Universität Linz, specializes in the field of Machine learning, Chemoinformatics.

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

Low-count time series anomaly detection

Improving few-and zero-shot reaction template prediction using modern hopfield networks

Understanding the effects of dataset characteristics on offline reinforcement learning

On failure modes in molecule generation and optimization

Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks

Philipp Renz Information

University

Position

___

Citations(all)

499

Citations(since 2020)

495

Cited By

108

hIndex(all)

5

hIndex(since 2020)

5

i10Index(all)

5

i10Index(since 2020)

5

Email

University Profile Page

Google Scholar

Philipp Renz Skills & Research Interests

Machine learning

Chemoinformatics

Top articles of Philipp Renz

Low-count time series anomaly detection

2023/9/17

Philipp Renz
Philipp Renz

H-Index: 3

Niall Twomey
Niall Twomey

H-Index: 12

Improving few-and zero-shot reaction template prediction using modern hopfield networks

2022/1/15

Understanding the effects of dataset characteristics on offline reinforcement learning

arXiv preprint arXiv:2111.04714

2021/10/12

On failure modes in molecule generation and optimization

2020/10/24

Large-scale ligand-based virtual screening for SARS-CoV-2 inhibitors using deep neural networks

arXiv preprint arXiv:2004.00979

2020/3/25

See List of Professors in Philipp Renz University(Johannes Kepler Universität Linz)

Co-Authors

academic-engine