357 citations · 1.2k across the 18 of their papers we have counts for
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Reweighted Manifold Learning of Collective Variables from Enhanced Sampling Simulations
Jakub Rydzewski, Ming Chen, Tushar K. Ghosh +1
Enhanced sampling methods are indispensable in computational physics and chemistry, where atomistic simulations cannot exhaustively sample the high-dimensional configuration space…
Improving the Efficiency of Variationally Enhanced Sampling with Wavelet-Based Bias Potentials
Benjamin Pampel, Omar Valsson
Collective variable-based enhanced sampling methods are routinely used on systems with metastable states, where high free energy barriers impede proper sampling of the free energy…
Multiscale reweighted stochastic embedding (MRSE): Deep learning of collective variables for enhanced sampling
Jakub Rydzewski, Omar Valsson
Machine learning methods provide a general framework for automatically finding and representing the essential characteristics of simulation data. This task is particularly crucial…
Chemical Potential Calculations in Non-Homogeneous Liquids
Claudio Perego, Omar Valsson, Michele Parrinello
The numerical computation of chemical potential in dense, non-homogeneous fluids is a key problem in the study of confined fluids thermodynamics. To this day several methods have b…
Frequency adaptive metadynamics for the calculation of rare-event kinetics
Yong Wang, Omar Valsson, Pratyush Tiwary +2
The ability to predict accurate thermodynamic and kinetic properties in biomolecular systems is of both scientific and practical utility. While both remain very difficult, predicti…
Conformational Entropy as Collective Variable for Proteins
Ferruccio Palazzesi, Omar Valsson, Michele Parrinello
Many enhanced sampling methods, such as Umbrella Sampling, Metadynamics or Variationally Enhanced Sampling, rely on the identification of appropriate collective variables. For prot…