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Explore machine learning approaches to improve density functional theory with Marivi Fernandez-Serra's lecture at IPAM. Learn about neural networks, physically informed machine learning, and more in under 1 hour.
Explore quantum mechanics with Lucas Wagner from the University of Illinois, focusing on compact representations of excited states from QMC. Offered by IPAM, it's under 1-hour long.
Explore quantum time correlation functions with Mark Tuckerman's lecture at IPAM, covering topics like path integrals, rate theory, and sampling methods. Less than 1-hour workload.
Explore E(3)-Equivariant Interatomic Potentials theory and applications with Ilyes Batatia from the University of Cambridge, offered by IPAM. Less than 1-hour workload.
Learn to approximate matrix eigenvalues using subspace iteration with repeated random sparsification from Robert Webber at IPAM. Ideal for high-dimensional problems.
Explore machine learning methods in photochemistry with Julia Westermayr from the University of Warwick, in a short program by IPAM at UCLA. Learn to predict excited states and understand light-matter interactions.
Explore high-accuracy wavefunctions using deep-learning-based variational Monte Carlo with Michael Scherbela from the University of Vienna, in a short program by IPAM.
Explore quantum mechanics with Kieron Burke's lecture on "Conditional probability density functional theory" from IPAM at UCLA. Dive into electronic structure calculations and their applications.
Explore quantum chemistry through neural-network wave functions with Jan Hermann of Freie Universität Berlin, in a less than 1-hour session by IPAM at UCLA.
Explore an algorithm for using multi Slater wavefunctions in AFQMC with Sandeep Sharma from the University of Colorado, Boulder, in this under 1-hour material from IPAM.
Explore machine learning applications in equation state and transport modeling at extreme conditions with Raymond Clay from Sandia National Laboratories, offered by IPAM.
Explore Stochastic Density Functional Theory with Eran Rabani from UC Berkeley, in a less than 1-hour session at IPAM, UCLA. Learn about ground-state properties, statistical errors, and mitigation strategies.
Explore machine learning and game theory's social impact with Fei Fang of Carnegie Mellon University, in a short program by IPAM at UCLA. Learn about real-world applications in security, environmental sustainability, and food security.
Explore collective intelligence through systems mathematics with David Spivak's talk at IPAM, UCLA. Understand how intelligence arises from simpler sense-making activities.
Explore collective (un)intelligence, innovation, and institutions with Jacob Foster from UCLA, in a short, impactful session offered by IPAM.
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