2 citations · 3 across the 6 of their papers we have counts for
6 papers
SwarmRL: Building the Future of Smart Active Systems
Samuel Tovey, Christoph Lohrmann, Tobias Merkt +6
This work introduces SwarmRL, a Python package designed to study intelligent active particles. SwarmRL provides an easy-to-use interface for developing models to control microscopi…
Emergence of Chemotactic Strategies with Multi-Agent Reinforcement Learning
Samuel Tovey, Christoph Lohrmann, Christian Holm
Reinforcement learning (RL) is a flexible and efficient method for programming micro-robots in complex environments. Here we investigate whether reinforcement learning can provide…
Emergence of Accurate Atomic Energies from Machine Learned Noble Gas Potentials
Frank Uhlig, Samuel Tovey, Christian Holm
The quantum theory of atoms in molecules (QTAIM) gives access to well-defined local atomic energies. Due to their locality, these energies are potentially interesting in fitting at…
ZnTrack -- Data as Code
Fabian Zills, Moritz Schäfer, Samuel Tovey +2
The past decade has seen tremendous breakthroughs in computation and there is no indication that this will slow any time soon. Machine learning, large-scale computing resources, an…
Generating Minimal Training Sets for Machine Learned Potentials
Jan Finkbeiner, Samuel Tovey, Christian Holm
This letter presents a novel approach for identifying uncorrelated atomic configurations from extensive data sets with a non-standard neural network workflow known as random networ…
Towards a Phenomenological Understanding of Neural Networks: Data
Samuel Tovey, Sven Krippendorf, Konstantin Nikolaou +1
A theory of neural networks (NNs) built upon collective variables would provide scientists with the tools to better understand the learning process at every stage. In this work, we…