251 citations · 880 across the 16 of their papers we have counts for
16 papers
Improved machine learning algorithm for predicting ground state properties
Laura Lewis, Hsin-Yuan Huang, Viet T. Tran +3
Finding the ground state of a quantum many-body system is a fundamental problem in quantum physics. In this work, we give a classical machine learning (ML) algorithm for predicting…
Residual Neural Networks for the Prediction of Planetary Collision Outcomes
Philip M. Winter, Christoph Burger, Sebastian Lehner +3
Fast and accurate treatment of collisions in the context of modern N-body planet formation simulations remains a challenging task due to inherently complex collision processes. We…
Few-Shot Learning by Dimensionality Reduction in Gradient Space
Martin Gauch, Maximilian Beck, Thomas Adler +10
We introduce SubGD, a novel few-shot learning method which is based on the recent finding that stochastic gradient descent updates tend to live in a low-dimensional parameter subsp…
History Compression via Language Models in Reinforcement Learning
Fabian Paischer, Thomas Adler, Vihang Patil +5
In a partially observable Markov decision process (POMDP), an agent typically uses a representation of the past to approximate the underlying MDP. We propose to utilize a frozen Pr…
Boundary Graph Neural Networks for 3D Simulations
Andreas Mayr, Sebastian Lehner, Arno Mayrhofer +3
The abundance of data has given machine learning considerable momentum in natural sciences and engineering, though modeling of physical processes is often difficult. A particularly…
Learning 3D Granular Flow Simulations
Andreas Mayr, Sebastian Lehner, Arno Mayrhofer +3
Recently, the application of machine learning models has gained momentum in natural sciences and engineering, which is a natural fit due to the abundance of data in these fields. H…