J
Javier Duarte
Researcher at University of California, San Diego
Publications - 12
Citations - 205
Javier Duarte is an academic researcher from University of California, San Diego. The author has contributed to research in topics: Graph (abstract data type) & Benchmark (computing). The author has an hindex of 6, co-authored 12 publications receiving 87 citations.
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The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics.
Gregor Kasieczka,Benjamin Philip Nachman,David Shih,Oz Amram,Anders Andreassen,Kees Benkendorder,Blaz Bortolato,Gustaaf Broojimans,Florencia Canelli,Jack H. Collins,Biwei Dai,Felipe F. Freitas,B. Dillon,Ioan-Mihail Dinu,Zhongtian Dong,Julien Donini,Javier Duarte,Darius A. Faroughy,Julia Lynne Gonski,Philip Harris,Alan Mathew Kahn,Jernej F. Kamenik,Charanjit K. Khosa,Patrick Komsike,Luc Le Pottier,Pablo Martin,Andrej Matevc,Eric M. Metodiev,Vinicius Massami Mikuni,Christopher W. Murphy,Ines Ochoa,Sang Eon Park,Maurizio Pierini,Dylan Rankin,Veronica Sanz,Nilai Sarda,Uroš Seljak,Aleks Smolkovič,George Stein,Cristina Mantilla Suarez,Manuel Szewc,Jesse Thaler,Steven Tsan,Silviu Udrescu,Louis Vaslin,Jean-Roch Vilmant,Daniel T. Williams,Mikaeel Yunus +47 more
TL;DR: The LHC Olympics 2020 as discussed by the authors is a community challenge accompanied by a set of simulated collider events, where participants have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly.
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The LHC Olympics 2020: A Community Challenge for Anomaly Detection in High Energy Physics
Gregor Kasieczka,Benjamin Philip Nachman,David Shih,Oz Amram,Anders Andreassen,Kees Benkendorfer,Blaz Bortolato,Gustaaf Brooijmans,Florencia Canelli,Jack H. Collins,Biwei Dai,Felipe F. Freitas,Barry M. Dillon,Ioan-Mihail Dinu,Zhongtian Dong,Julien Donini,Javier Duarte,Darius A. Faroughy,Julia Lynne Gonski,Philip Harris,Alan Mathew Kahn,Jernej F. Kamenik,Charanjit K. Khosa,Patrick T. Komiske,Luc Le Pottier,Pablo Martín-Ramiro,Andrej Matevc,Eric M. Metodiev,Vinicius Massami Mikuni,I. Ochoa,Sang Eon Park,Maurizio Pierini,Dylan Rankin,Veronica Sanz,Nilai Sarda,Urous Seljak,Aleks Smolkovič,George Stein,Cristina Mantilla Suarez,Manuel Szewc,Jesse Thaler,Steven Tsan,Silviu-Marian Udrescu,Louis Vaslin,Jean-Roch Vlimant,Daniel T. Williams,Mikaeel Yunus +46 more
TL;DR: The LHC Olympics 2020 as mentioned in this paper is a community challenge accompanied by a set of simulated collider events, where participants have developed their methods using an R&D dataset and then tested them on black boxes: datasets with an unknown anomaly.
Journal ArticleDOI
Fast convolutional neural networks on FPGAs with hls4ml
Thea Klaeboe Aarrestad,Vladimir Loncar,Nicolò Ghielmetti,Maurizio Pierini,Sioni Summers,Jennifer Ngadiuba,Christoffer Petersson,Hampus Linander,Yutaro Iiyama,Giuseppe Di Guglielmo,Javier Duarte,Philip Harris,Dylan Rankin,Sergo Jindariani,Kevin Pedro,Nhan Tran,Mia Liu,Edward Kreinar,Zhenbin Wu,Duc Hoang +19 more
TL;DR: In this paper, an automated tool for deploying ultra low-latency, low-power deep neural networks with convolutional layers on field-programmable gate arrays (FPGAs) is introduced.
Journal ArticleDOI
MLPF: efficient machine-learned particle-flow reconstruction using graph neural networks
TL;DR: In this paper, an end-to-end trainable, machine-learned particle-flow algorithm based on parallelizable, computationally efficient, and scalable graph neural network optimized using a multi-task objective on simulated events is presented.
Charged Particle Tracking via Edge-Classifying Interaction Networks
Gage Dezoort,Savannah Thais,Javier Duarte,Vesal Razavimaleki,Markus Atkinson,Isobel Ojalvo,Mark Neubauer,Peter Elmer +7 more
TL;DR: In this article, the authors adapt the physics-motivated interaction network (IN) GNN to the problem of particle tracking in pileup conditions similar to those expected at the high-luminosity Large Hadron Collider.