activity
20152024
most citedHeuristics-Guided Exploration of Reaction Mechanisms

178 citations · 469 across the 8 of their papers we have counts for

collaborators

8 papers

cs.LG2024

regAL: Python Package for Active Learning of Regression Problems

Elizaveta Surzhikova, Jonny Proppe

Increasingly more research areas rely on machine learning methods to accelerate discovery while saving resources. Machine learning models, however, usually require large datasets o…

cs.SE2019★ 21 cited

A multi-label, dual-output deep neural network for automated bug triaging

Christopher A. Choquette-Choo, David Sheldon, Jonny Proppe +2

Bug tracking enables the monitoring and resolution of issues and bugs within organizations. Bug triaging, or assigning bugs to the owner(s) who will resolve them, is a critical com…

physics.chem-ph2019★ 63 cited

Gaussian Process-Based Refinement of Dispersion Corrections

Jonny Proppe, Stefan Gugler, Markus Reiher

We employ Gaussian process (GP) regression to adjust for systematic errors in D3-type dispersion corrections introducing the associated, statistically improved model D3-GP. We gene…

physics.chem-ph2018★ 59 cited

Mechanism Deduction from Noisy Chemical Reaction Networks

Jonny Proppe, Markus Reiher

We introduce KiNetX, a fully automated meta-algorithm for the kinetic analysis of complex chemical reaction networks derived from semi-accurate but efficient electronic structure c…

physics.chem-ph2018★ 33 cited

Statistical Analysis of Semiclassical Dispersion Corrections

Thomas Weymuth, Jonny Proppe, Markus Reiher

Semiclassical dispersion corrections developed by Grimme and coworkers have become indispensable in applications of Kohn-Sham density functional theory. We present an in-depth asse…

physics.chem-ph2017★ 63 cited

Reliable estimation of prediction uncertainty for physico-chemical property models

Jonny Proppe, Markus Reiher

The predictions of parameteric property models and their uncertainties are sensitive to systematic errors such as inconsistent reference data, parametric model assumptions, or inad…

physics.chem-ph2017★ 52 cited

Error Assessment of Computational Models in Chemistry

Gregor N. Simm, Jonny Proppe, Markus Reiher

Computational models in chemistry rely on a number of approximations. The effect of such approximations on observables derived from them is often unpredictable. Therefore, it is ch…

physics.chem-ph2015★ 178 cited

Heuristics-Guided Exploration of Reaction Mechanisms

Maike Bergeler, Gregor N. Simm, Jonny Proppe +1

For the investigation of chemical reaction networks, the efficient and accurate determination of all relevant intermediates and elementary reactions is mandatory. The complexity of…