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Large-scale graph representation learning with very deep GNNs and self-supervision



Ravichandra Addanki , Peter W. Battaglia , David Budden , Andreea Deac , Jonathan Godwin , Thomas Keck , Wai Lok Sibon Li , Alvaro Sanchez-Gonzalez , Jacklynn Stott , Shantanu Thakoor , Petar Veličković

* To appear at KDD Cup 2021. 13 pages, 3 figures. All authors contributed equally 

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Podracer architectures for scalable Reinforcement Learning



Matteo Hessel , Manuel Kroiss , Aidan Clark , Iurii Kemaev , John Quan , Thomas Keck , Fabio Viola , Hado van Hasselt


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Solving Mixed Integer Programs Using Neural Networks



Vinod Nair , Sergey Bartunov , Felix Gimeno , Ingrid von Glehn , Pawel Lichocki , Ivan Lobov , Brendan O'Donoghue , Nicolas Sonnerat , Christian Tjandraatmadja , Pengming Wang , Ravichandra Addanki , Tharindi Hapuarachchi , Thomas Keck , James Keeling , Pushmeet Kohli , Ira Ktena , Yujia Li , Oriol Vinyals , Yori Zwols


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Machine Learning in High Energy Physics Community White Paper



Kim Albertsson , Piero Altoe , Dustin Anderson , Michael Andrews , Juan Pedro Araque Espinosa , Adam Aurisano , Laurent Basara , Adrian Bevan , Wahid Bhimji , Daniele Bonacorsi , Paolo Calafiura , Mario Campanelli , Louis Capps , Federico Carminati , Stefano Carrazza , Taylor Childers , Elias Coniavitis , Kyle Cranmer , Claire David , Douglas Davis , Javier Duarte , Martin Erdmann , Jonas Eschle , Amir Farbin , Matthew Feickert , Nuno Filipe Castro , Conor Fitzpatrick , Michele Floris , Alessandra Forti , Jordi Garra-Tico , Jochen Gemmler , Maria Girone , Paul Glaysher , Sergei Gleyzer , Vladimir Gligorov , Tobias Golling , Jonas Graw , Lindsey Gray , Dick Greenwood , Thomas Hacker , John Harvey , Benedikt Hegner , Lukas Heinrich , Ben Hooberman , Johannes Junggeburth , Michael Kagan , Meghan Kane , Konstantin Kanishchev , Przemysław Karpiński , Zahari Kassabov , Gaurav Kaul , Dorian Kcira , Thomas Keck , Alexei Klimentov , Jim Kowalkowski , Luke Kreczko , Alexander Kurepin , Rob Kutschke , Valentin Kuznetsov , Nicolas Köhler , Igor Lakomov , Kevin Lannon , Mario Lassnig , Antonio Limosani , Gilles Louppe , Aashrita Mangu , Pere Mato , Narain Meenakshi , Helge Meinhard , Dario Menasce , Lorenzo Moneta , Seth Moortgat , Mark Neubauer , Harvey Newman , Hans Pabst , Michela Paganini , Manfred Paulini , Gabriel Perdue , Uzziel Perez , Attilio Picazio , Jim Pivarski , Harrison Prosper , Fernanda Psihas , Alexander Radovic , Ryan Reece , Aurelius Rinkevicius , Eduardo Rodrigues , Jamal Rorie , David Rousseau , Aaron Sauers , Steven Schramm , Ariel Schwartzman , Horst Severini , Paul Seyfert , Filip Siroky , Konstantin Skazytkin , Mike Sokoloff , Graeme Stewart , Bob Stienen , Ian Stockdale , Giles Strong , Savannah Thais , Karen Tomko , Eli Upfal , Emanuele Usai , Andrey Ustyuzhanin , Martin Vala , Sofia Vallecorsa , Mauro Verzetti , Xavier Vilasís-Cardona , Jean-Roch Vlimant , Ilija Vukotic , Sean-Jiun Wang , Gordon Watts , Michael Williams , Wenjing Wu , Stefan Wunsch , Omar Zapata

* Editors: Sergei Gleyzer, Paul Seyfert and Steven Schramm 

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FastBDT: A speed-optimized and cache-friendly implementation of stochastic gradient-boosted decision trees for multivariate classification



Thomas Keck


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