5 papers
Towards Scalable Proteomics: Opportunistic SMC Samplers on HTCondor
Matthew Carter, Lee Devlin, Alexander Philips +3
Quantitative proteomics plays a central role in uncovering regulatory mechanisms, identifying disease biomarkers, and guiding the development of precision therapies. These insights…
MACS: Multi-Agent Reinforcement Learning for Optimization of Crystal Structures
Elena Zamaraeva, Christopher M. Collins, George R. Darling +8
Geometry optimization of atomic structures is a common and crucial task in computational chemistry and materials design. Following the learning to optimize paradigm, we propose a n…
Fast and Near-Optimal Collision-Free Robot Scheduling On Paths
Duncan Adamson, Nathan Flaherty, Igor Potapov +2
In this paper, we address the problem of scheduling a set of robots to complete tasks in a laboratory environment, modelled as a graph, while avoiding collisions. We analyze the dy…
Distributed weak independent sets in hypergraphs: Upper and lower bounds
Duncan Adamson, Will Rosenbaum, Paul G. Spirakis
In this paper, we consider the problem of finding weak independent sets in a distributed network represented by a hypergraph. In this setting, each edge contains a set of r vertice…
Collision-Free Robot Scheduling
Duncan Adamson, Nathan Flaherty, Igor Potapov +1
Robots are becoming an increasingly common part of scientific work within laboratory environments. In this paper, we investigate the problem of designing \emph{schedules} for compl…