231 citations · 348 across the 10 of their papers we have counts for
6 papers · 1 filter
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…
Environmental effects on emergent strategy in micro-scale multi-agent reinforcement learning
Samuel Tovey, David Zimmer, Christoph Lohrmann +5
Multi-Agent Reinforcement Learning (MARL) is a promising candidate for realizing efficient control of microscopic particles, of which micro-robots are a subset. However, the micros…
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…
A Generalized Grand-Reaction Method for Modelling the Exchange of Weak (Polyprotic) Acids between a Solution and a Weak Polyelectrolyte Phase
David Beyer, Christian Holm
We introduce a Monte-Carlo method that allows for the simulation of a polymeric phase containing a weak polyelectrolyte, which is coupled to a reservoir at a fixed pH, salt concent…
Explaining Giant Apparent Shifts in Weak Polyelectrolyte Brushes
David Beyer, Peter Košovan, Christian Holm
Recent experiments on weak polyelectrolyte brushes found marked shifts in the effective p that are linear in the logarithm of the salt concentration. Comparing explic…
Optimal motility strategies for self-propelled agents to explore porous media
Christoph Lohrmann, Christian Holm
Micro-robots for, e.g., biomedical applications, need to be equipped with motility strategies that enable them to navigate through complex environments. Inspired by biological micr…