172 citations · 551 across the 12 of their papers we have counts for
12 papers
Estimating Gibbs free energies via isobaric-isothermal flows
Peter Wirnsberger, Borja Ibarz, George Papamakarios
We present a machine-learning model based on normalizing flows that is trained to sample from the isobaric-isothermal ensemble. In our approach, we approximate the joint distributi…
GraphCast: Learning skillful medium-range global weather forecasting
Remi Lam, Alvaro Sanchez-Gonzalez, Matthew Willson +15
Global medium-range weather forecasting is critical to decision-making across many social and economic domains. Traditional numerical weather prediction uses increased compute reso…
MultiScale MeshGraphNets
Meire Fortunato, Tobias Pfaff, Peter Wirnsberger +2
In recent years, there has been a growing interest in using machine learning to overcome the high cost of numerical simulation, with some learned models achieving impressive speed-…
SyMetric: Measuring the Quality of Learnt Hamiltonian Dynamics Inferred from Vision
Irina Higgins, Peter Wirnsberger, Andrew Jaegle +1
A recently proposed class of models attempts to learn latent dynamics from high-dimensional observations, like images, using priors informed by Hamiltonian mechanics. While these m…
Which priors matter? Benchmarking models for learning latent dynamics
Aleksandar Botev, Andrew Jaegle, Peter Wirnsberger +2
Learning dynamics is at the heart of many important applications of machine learning (ML), such as robotics and autonomous driving. In these settings, ML algorithms typically need…
Normalizing flows for atomic solids
Peter Wirnsberger, George Papamakarios, Borja Ibarz +4
We present a machine-learning approach, based on normalizing flows, for modelling atomic solids. Our model transforms an analytically tractable base distribution into the target so…
Targeted free energy estimation via learned mappings
Peter Wirnsberger, Andrew J. Ballard, George Papamakarios +5
Free energy perturbation (FEP) was proposed by Zwanzig more than six decades ago as a method to estimate free energy differences, and has since inspired a huge body of related meth…
Microscopic analysis of thermo-orientation in systems of off-centre Lennard-Jones particles
Robert L. Jack, Peter Wirnsberger, Aleks Reinhardt
When fluids of anisotropic molecules are placed in temperature gradients, the molecules may align themselves along the gradient: this is called thermo-orientation. We discuss the t…
Theoretical prediction of thermal polarisation
Peter Wirnsberger, Christoph Dellago, Daan Frenkel +1
We present a mean-field theory to explain the thermo-orientation effect in an off-centre Stockmayer fluid. This effect is the underlying cause of thermally induced polarisation and…
Controlling cargo trafficking in multicomponent membranes
Tine Curk, Peter Wirnsberger, Jure Dobnikar +2
Biological membranes typically contain a large number of different components dispersed in small concentrations in the main membrane phase, including proteins, sugars, and lipids o…
Numerical Evidence for Thermally Induced Monopoles
Peter Wirnsberger, Domagoj Fijan, Roger Adam Lightwood +3
Electrical charges are conserved. The same would be expected to hold for magnetic charges, yet magnetic monopoles have never been observed. It is therefore surprising that the laws…
An enhanced version of the heat exchange algorithm with excellent energy conservation properties
P. Wirnsberger, D. Frenkel, C. Dellago
We propose a new algorithm for non-equilibrium molecular dynamics simulations of thermal gradients. The algorithm is an extension of the heat exchange algorithm developed by Hafskj…