Fetching the paper…
Reading the bibliography…
Neutrino experiments study the least understood of the Standard Model particles by observing their direct interactions with matter or searching for ultra-rare signals.
Principal Component Analysis and Factor Analysis
I. T. Jolliffe · 1986
Earlier work this paper cites.
Neutrino oscillations and the solar neutrino problem
M E Berbenni Bitsch and A Vancura · 1989
Earlier work this paper cites.
Finding Gluon Jets With a Neural Trigger
Leif Lonnblad, Carsten Peterson, and Thorsteinn Rognvaldsson · 1990
Earlier work this paper cites.
Signature verification using a ”siamese” time delay neural network
Jane Bromley, Isabelle Guyon, Yann LeCun, Eduard Säckinger, and Roopak Shah · 1993
Earlier work this paper cites.
ROOT: An object oriented data analysis framework
R. Brun and F. Rademakers · 1997
Earlier work this paper cites.
Evidence for oscillation of atmospheric neutrinos
Y. Fukuda et al · 1998
Earlier work this paper cites.
Electron energy spectra, fluxes, and day-night asymmetries of B-8 solar neutrinos from measurements with NaCl dissolved in the heavy-water detector at the Sudbury Neutrino Observatory
B. Aharmim et al · 2005
Earlier work this paper cites.
Connecting low energy leptonic CP-violation to leptogenesis
S. Pascoli et al · 2007
Earlier work this paper cites.
Visualizing high-dimensional data using t-sne
L.J.P. van der Maaten and G.E. Hinton · 2008
Earlier work this paper cites.
ImageNet: A Large-Scale Hierarchical Image Database
J. Deng et al · 2009
Earlier work this paper cites.
NEXT-100 Technical Design Report (TDR): Executive Summary
V. Alvarez et al · 2012
Earlier work this paper cites.
The MicroBooNE Technical Design Report
Bonnie Fleming · 2012
Earlier work this paper cites.
Deep inside convolutional networks: Visualising image classification models and saliency maps, 2013
Karen Simonyan, Andrea Vedaldi, and Andrew Zisserman · 2013
Earlier work this paper cites.
Building for Discovery: Strategic Plan for U.S. Particle Physics in the Global Context, institution = U.S. Department of Energy and National Science Foundation
S. Ritz et al · 2014
Earlier work this paper cites.
Going deeper with convolutions, 2014
C. Szegedy et al · 2014
Earlier work this paper cites.
Deep learning for visual understanding: A review
Y. Guo et al · 2015
Earlier work this paper cites.
Deep learning in neural networks: An overview
Jürgen Schmidhuber · 2015
Earlier work this paper cites.
An introduction to convolutional neural networks, 2015
Keiron O’Shea and Ryan Nash · 2015
Earlier work this paper cites.
ImageNet Large Scale Visual Recognition Challenge
O. Russakovsky et al · 2015
Earlier work this paper cites.
Domain-adversarial training of neural networks, 2015
Y. Ganin et al · 2015
Earlier work this paper cites.
Muon Neutrino to Electron Neutrino Oscillation in NO ν \nu A
Kanika Sachdev · 2015
Cited alongside, same era.
A convolutional neural network neutrino event classifier
A. Aurisano et al · 2016
Cited alongside, same era.
Search for Majorana Neutrinos near the Inverted Mass Hierarchy Region with KamLAND-Zen
A. Gando et al · 2016
Cited alongside, same era.
An overview of the daya bay reactor neutrino experiment
Jun Cao and Kam-Biu Luk · 2016
Cited alongside, same era.
Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks
E. Racah et al · 2016
Cited alongside, same era.
The ethics of algorithms: Mapping the debate
B. Mittelstadt et al · 2016
Cited alongside, same era.
Suppression of cosmic muon spallation backgrounds in liquid scintillator detectors using convolutional neural networks
A. Li, A. Elagin, S. Fraker, C. Grant, and L. Winslow · 2019
Later among the works it cites.
A survey on bias and fairness in machine learning, 2019
N. Mehrabi et al · 2019
Later among the works it cites.
Search for neutrinoless double- β \beta decay with the complete exo-200 dataset
G. Anton et al · 2019
Later among the works it cites.
Deep neural network for pixel-level electromagnetic particle identification in the microboone liquid argon time projection chamber
C. Adams et al · 2019
Later among the works it cites.
The short-baseline neutrino program at fermilab
Pedro A.N. Machado, Ornella Palamara, and David W. Schmitz · 2019
Later among the works it cites.
Dune as the next-generation solar neutrino experiment
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
European Astroparticle Physics Strategy 2017-2026
APPEC · 2017
Cited alongside, same era.
Background rejection in NEXT using deep neural networks
J. Renner et al · 2017
Cited alongside, same era.
Constraints on Oscillation Parameters from ν e \nu_{e} Appearance and ν μ \nu_{\mu} Disappearance in NOvA
P. Adamson et al · 2017
Cited alongside, same era.
Comparing deep neural networks against humans: object recognition when the signal gets weaker, 2017
Robert Geirhos, David H. J. Janssen, Heiko H. Schütt, Jonas Rauber, Matthias Bethge, and Felix A. Wichmann · 2017
Cited alongside, same era.
Activation functions: Comparison of trends in practice and research for deep learning, 2018
Chigozie Nwankpa, Winifred Ijomah, Anthony Gachagan, and Stephen Marshall · 2018
Cited alongside, same era.
The history began from alexnet: A comprehensive survey on deep learning approaches, 2018
Md Zahangir Alom et al · 2018
Cited alongside, same era.
Francesco Capozzi, Shirley Weishi Li, Guanying Zhu, and John F. Beacom · 2019
Later among the works it cites.
Accelerating deep neural networks for real-time data selection for high-resolution imaging particle detectors
Y. Jwa, G. Di Guglielmo, L. P. Carloni, and G. Karagiorgi · 2019
Later among the works it cites.
The global landscape of ai ethics guidelines
Anna Jobin, Marcello Ienca, and Effy Vayena · 2019
Later among the works it cites.
Context-enriched identification of particles with a convolutional network for neutrino events
F. Psihas et al · 2019
Later among the works it cites.
Detection of cosmic muon spallation background in ls-detector using machine learning
Zhenghao Fu · 2020
Closest in time.
American artificial inteligence initiative: Year one report
The White House Office of Science and Technology · 2020
Closest in time.
Bayesian neural networks, 2020
Tom Charnock, Laurence Perreault-Levasseur, and François Lanusse · 2020
Closest in time.
Uncertainty estimation for deep learning in neutrino physics
Aashwin Mishra · 2020
Closest in time.
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume I Introduction to DUNE
Babak Abi et al · 2020
Closest in time.
Neutrino interaction classification with a convolutional neural network in the dune far detector, 2020
B. Abi et al · 2020
Closest in time.
Scalable deep convolutional neural networks for sparse, locally dense liquid argon time projection chamber data
Laura Dominé and Kazuhiro Terao · 2020
Closest in time.
http://deeplearnphysics.org/DataChallenge/
Deep learn physics public dataset · 2020
Closest in time.
Deep Underground Neutrino Experiment (DUNE), Far Detector Technical Design Report, Volume I Introduction to DUNE
Babak Abi et al · 2020
Closest in time.
Dune-beta: Can we expand dune’s physics program to search for neurtino-less double beta decay?
J. Zennamo et al · 2020
Closest in time.