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Contributed talk - Unsupervised Resource Allocation with Graph Neural Networks
Miles Cranmer
Fri Dec 11 11:06 AM -- 11:11 AM (PST) @
Author Information
Miles Cranmer (Princeton University)
Miles Cranmer is an Astro PhD candidate trying to accelerate astrophysics with AI. Miles is from Canada and did his undergraduate in Physics at McGill. He is deeply interested in the automation of science, particularly aspects that are not yet tractable with existing machine learning, such as experiment planning, simulation, and theory. He works on symbolic regression, graph neural networks, normalizing flows, and learned simulation. He is hugely interested in symbolic ML, since, as he argues, symbolic models seem to be a surprisingly efficient basis for describing our universe.
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Eric Metodiev · Keming Zhang · Markus Stoye · Randy Churchill · Soumalya Sarkar · Miles Cranmer · Johann Brehmer · Danilo Jimenez Rezende · Peter Harrington · AkshatKumar Nigam · Nils Thuerey · Lukasz Maziarka · Alvaro Sanchez Gonzalez · Atakan Okan · James Ritchie · N. Benjamin Erichson · Harvey Cheng · Peihong Jiang · Seong Ho Pahng · Samson Koelle · Sami Khairy · Adrian Pol · Rushil Anirudh · Jannis Born · Benjamin Sanchez-Lengeling · Brian Timar · Rhys Goodall · Tamás Kriváchy · Lu Lu · Thomas Adler · Nathaniel Trask · Noëlie Cherrier · Tomohiko Konno · Muhammad Kasim · Tobias Golling · Zaccary Alperstein · Andrei Ustyuzhanin · James Stokes · Anna Golubeva · Ian Char · Ksenia Korovina · Youngwoo Cho · Chanchal Chatterjee · Tom Westerhout · Gorka Muñoz-Gil · Juan Zamudio-Fernandez · Jennifer Wei · Brian Lee · Johannes Kofler · Bruce Power · Nikita Kazeev · Andrey Ustyuzhanin · Artem Maevskiy · Pascal Friederich · Arash Tavakoli · Willie Neiswanger · Bohdan Kulchytskyy · sindhu hari · Paul Leu · Paul Atzberger