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Brian Nord

Fermilab

Unsupervised Resource Allocation with Graph Neural Networks

Jun 17, 2021
Miles Cranmer, Peter Melchior, Brian Nord

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* Accepted to PMLR/contributed oral at NeurIPS 2020 Pre-registration Workshop. Code at https://github.com/MilesCranmer/gnn_resource_allocation

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Deep learning insights into cosmological structure formation

Nov 20, 2020
Luisa Lucie-Smith, Hiranya V. Peiris, Andrew Pontzen, Brian Nord, Jeyan Thiyagalingam

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* 15 pages, 6 figures, to be submitted to Nature Communications, comments welcome

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Deeply Uncertain: Comparing Methods of Uncertainty Quantification in Deep Learning Algorithms

May 04, 2020
João Caldeira, Brian Nord

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* 11 pages, 3 figures; Presented at ICLR 2020 Workshop on Fundamental Science in the era of AI

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Restricted Boltzmann Machines for galaxy morphology classification with a quantum annealer

Nov 14, 2019
João Caldeira, Joshua Job, Steven H. Adachi, Brian Nord, Gabriel N. Perdue

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* 13 pages; LaTeX; 11 figures

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Algorithms and Statistical Models for Scientific Discovery in the Petabyte Era

Nov 05, 2019
Brian Nord, Andrew J. Connolly, Jamie Kinney, Jeremy Kubica, Gautaum Narayan, Joshua E. G. Peek, Chad Schafer, Erik J. Tollerud, Camille Avestruz, G. Jogesh Babu, Simon Birrer, Douglas Burke, João Caldeira, Douglas A. Caldwell, Joleen K. Carlberg, Yen-Chi Chen, Chuanfei Dong, Eric D. Feigelson, V. Zach Golkhou, Vinay Kashyap, T. S. Li, Thomas Loredo, Luisa Lucie-Smith, Kaisey S. Mandel, J. R. Martínez-Galarza, Adam A. Miller, Priyamvada Natarajan, Michelle Ntampaka, Andy Ptak, David Rapetti, Lior Shamir, Aneta Siemiginowska, Brigitta M. Sipőcz, Arfon M. Smith, Nhan Tran, Ricardo Vilalta, Lucianne M. Walkowicz, John ZuHone

* arXiv admin note: substantial text overlap with arXiv:1905.05116

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