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Explore quantum walk algorithms with Jingbo Wang from the University of Western Australia, in a less than 1-hour presentation at IPAM, UCLA. Delve into efficient quantum circuit design and potential applications.
Explore pricing strategies in online marketplaces with Stanford's Ellen Vitercik in this under 1-hour material from IPAM. Learn to balance high prices and customer reviews through online learning algorithms.
Explore efficient matrix multiplication algorithms with RL in a less than 1-hour session by Matej Balog of DeepMind, presented at IPAM's AI and Discrete Optimization Workshop.
Explore machine learning for MIP solving with Bistra Dilkina at IPAM's AI and Discrete Optimization Workshop. Less than 1-hour material.
Explore Google Brain's Vinod Nair's presentation on leveraging neural network accelerators for Maximum Satisfiability problems, offered by IPAM at UCLA.
Explore the aesthetics of formalized mathematics with Heather Macbeth's presentation at IPAM, UCLA, focusing on algorithms and abstractions in proofs.
Learn from James Davenport's presentation at IPAM's Machine Assisted Proofs Workshop on proving calculation correctness, with a focus on real algebraic geometry. Less than 1-hour material.
Explore SMT solving and quantifier reasoning with Pascal Fontaine from Université de Liège, in a short session by IPAM, UCLA. Delve into future developments in SMT.
Explore computational perspectives in mathematics and computer science with Anne Baanen's talk at IPAM, UCLA. Delve into class number computations and Lean library use.
Explore SMT solvers and machine-checkable certificates with Haniel Barbosa in a short lecture from IPAM, UCLA. Learn about cvc5's proof-production infrastructure redesign.
Explore the intersection of deep learning and mathematics with Geordie Williamson in this less than 1-hour material from IPAM at UCLA.
Explore chemical compound space with Anatole von Lilienfeld's presentation at IPAM's workshop. Gain insights into atomistic structure, quantum mechanics, and machine learning.
Explore the integration of symmetries into deep neural networks for improved physical consistency and efficiency with Rose Yu at IPAM, UCLA. Duration: 1-2 hours.
Explore lab-in-the-loop antibody design and its computational aspects with Kyunghyun Cho from NYU, in a 1-2 hour session offered by IPAM.
Explore machine learning force fields for large molecular systems with Stefan Chmiela in this short session from IPAM. Dive into the challenges and research directions for accurate global MLFFs.
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