129 citations · 421 across the 9 of their papers we have counts for
16 papers
Accurate Computation of Quantum Excited States with Neural Networks
David Pfau, Simon Axelrod, Halvard Sutterud +2
We present a variational Monte Carlo algorithm for estimating the lowest excited states of a quantum system which is a natural generalization of the estimation of ground states. Th…
Neural Wave Functions for Superfluids
Wan Tong Lou, Halvard Sutterud, Gino Cassella +4
Understanding superfluidity remains a major goal of condensed matter physics. Here we tackle this challenge utilizing the recently developed Fermionic neural network (FermiNet) wav…
A Self-Attention Ansatz for Ab-initio Quantum Chemistry
Ingrid von Glehn, James S. Spencer, David Pfau
We present a novel neural network architecture using self-attention, the Wavefunction Transformer (Psiformer), which can be used as an approximation (or Ansatz) for solving the man…
Ab-initio quantum chemistry with neural-network wavefunctions
Jan Hermann, James Spencer, Kenny Choo +5
Machine learning and specifically deep-learning methods have outperformed human capabilities in many pattern recognition and data processing problems, in game playing, and now also…
Discovering Quantum Phase Transitions with Fermionic Neural Networks
G. Cassella, H. Sutterud, S. Azadi +4
Deep neural networks have been extremely successful as highly accurate wave function ansätze for variational Monte Carlo calculations of molecular ground states. We present an exte…
Integrable Nonparametric Flows
David Pfau, Danilo Rezende
We introduce a method for reconstructing an infinitesimal normalizing flow given only an infinitesimal change to a (possibly unnormalized) probability distribution. This reverses t…