49 citations · 113 across the 6 of their papers we have counts for
3 papers · 1 filter
RuNNer 2.0: A Software Suite for High-Dimensional Neural Network Potentials
Alexander L. M. Knoll, Moritz R. Schäfer, K. Nikolas Lausch +11
We present RuNNer 2.0, the "Ruhr University Neural Network energy representation", a highly optimized software suite for training and evaluating high-dimensional neural network pot…
Machine learning potentials for redox chemistry in solution
Emir Kocer, Redouan El Haouari, Christoph Dellago +1
Machine learning potentials (MLPs) represent atomic interactions with quantum mechanical accuracy offering an efficient tool for atomistic simulations in many fields of science. Ho…
Neural Network Potentials: A Concise Overview of Methods
Emir Kocer, Tsz Wai Ko, Jörg Behler
In the past two decades, machine learning potentials (MLP) have reached a level of maturity that now enables applications to large-scale atomistic simulations of a wide range of sy…