108 citations · 108 across the 1 of their papers we have counts for
4 papers
Training atomic neural networks using fragment-based data generated in virtual reality
Silvia Amabilino, Lars A. Bratholm, Simon J. Bennie +2
The ability to understand and engineer molecular structures relies on having accurate descriptions of the energy as a function of atomic coordinates. Here we outline a new paradigm…
IMPRESSION -- Prediction of NMR Parameters for 3-dimensional chemical structures using Machine Learning with near quantum chemical accuracy
Will Gerrard, Lars Andersen Bratholm, Martin Packer +3
The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar Information Of Nuclei) machine learning system provides an efficient and accurate route to the prediction of NMR…
Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality
Silvia Amabilino, Lars A. Bratholm, Simon J. Bennie +3
Whilst the primary bottleneck to a number of computational workflows was not so long ago limited by processing power, the rise of machine learning technologies has resulted in a pa…
Sonifying stochastic walks on biomolecular energy landscapes
Robert E. Arbon, Alex J. Jones, Lars A. Bratholm +2
Translating the complex, multi-dimensional data from simulations of biomolecules to intuitive knowledge is a major challenge in computational chemistry and biology. The so-called "…