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David Ceperley - Quantum Monte Carlo and Machine Learning Simulations of Dense Hydrogen
Presenter
- David Ceperley
May 26, 2022
IPAM
Mark Tuckerman - Quantum time correlation functions in an open-chain path integral distribution
Presenter
- Mark Tuckerman
May 26, 2022
IPAM
Lucas Wagner - Compact representations of excited states from QMC, as data for low-energy models
Presenter
- Lucas Wagner
May 26, 2022
IPAM
Marivi Fernandez Serra - Machine learning to improve the exchange and correlation functional in DFT
Presenter
- Marivi Fernandez-Serra
May 26, 2022
IPAM
Bryan Clark - Variational Wavefunctions, Machine Learning Architecture for Fermions & Gauge Theories
Presenter
- Bryan Clark
May 26, 2022
IPAM
Brenda Rubenstein - Extending the Reach of Quantum Monte Carlo Methods via Machine Learning
Presenter
- Brenda Rubenstein
May 26, 2022
IPAM
Jan Hermann - Neural-network wave functions for quantum chemistry
Presenter
- Jan Hermann
May 25, 2022
IPAM
Anouar Benali - multideterminant many-body methods to describe ground and excited state properties
Presenter
- Anouar Benali
May 25, 2022
IPAM
Robert Webber - Approximate matrix eigenvalues, subspace iteration w/ repeated random sparsification
Presenter
- Robert Webber
May 25, 2022
IPAM
Andrea Tirelli - Monte Carlo and Machine Learning Approaches in Quantum Mechanics - IPAM at UCLA
Presenter
- Andrea Tirelli
May 25, 2022
IPAM
Giuseppe Carleo - Fermionic neural-network quantum states
Presenter
- Giuseppe Carleo
May 24, 2022
IPAM