Fetching the paper…
Reading the bibliography…
We present a neural network architecture that is fully equivariant with respect to transformations under the Lorentz group, a fundamental symmetry of space and time in physics.
“The Classical Groups. Their Invariants and Representations”
Hermann Weyl · 1946
Earlier work this paper cites.
“Representations of the Rotation and Lorentz Groups and Their Applications”, Graduate Texts in Mathematics
I.. Gelfand, R.. Minlos and Z.. Shapiro · 1963
Earlier work this paper cites.
“Invariant tensor fields in physics and the classical groups”
Willard Miller Jr · 1971
Earlier work this paper cites.
“Theory of group representations and applications”
Asim. Barut and Ryszard Raczka · 1977
Earlier work this paper cites.
“Group representations in probability and statistics” 11
Persi Diaconis · 1988
Earlier work this paper cites.
“Zeros of equivariant vector fields: algorithms for an invariant approach”
Patrick. Worfolk · 1994
Earlier work this paper cites.
“Representation of Lie groups and special functions” Recent advances, Translated from the Russian manuscript by V. A. Groza and A. A. Groza 316
N.. Vilenkin and A.. Klimyk · 1995
Earlier work this paper cites.
“The geometry of physics” An introduction
Theodore Frankel · 2004
Earlier work this paper cites.
“The ATLAS Experiment at the CERN Large Hadron Collider”
ATLAS Collaboration · 2008
Earlier work this paper cites.
“The Anti-k(t) jet clustering algorithm”
Matteo Cacciari, Gavin. Salam and Gregory Soyez · 2008
Earlier work this paper cites.
“The CMS experiment at the CERN LHC”
CMS Collaboration · 2008
Earlier work this paper cites.
“Symmetry, representations, and invariants” 255
Roe Goodman and Nolan. Wallach · 2009
Earlier work this paper cites.
“Towards Jetography”
Gavin. Salam · 2010
Earlier work this paper cites.
“Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC”
ATLAS Collaboration · 2012
Earlier work this paper cites.
“Observation of a New Boson at a Mass of 125 GeV with the CMS Experiment at the LHC”
CMS Collaboration · 2012
Earlier work this paper cites.
“Spectral Networks and Locally Connected Networks on Graphs”
Joan Bruna, Wojciech Zaremba, Arthur Szlam and Yann LeCun · 2014
Earlier work this paper cites.
“DELPHES 3, A modular framework for fast simulation of a generic collider experiment”
J. de Favereau, C. Delaere, P. Demin, A. Giammanco, V. Lemaître, A. Mertens and M. Selvaggi · 2014
Cited alongside, same era.
“Visualizing and Understanding Convolutional Networks”
Matthew. Zeiler and Rob Fergus · 2014
Cited alongside, same era.
“Lie groups, Lie algebras, and representations” An elementary introduction 222
Brian Hall · 2015
Cited alongside, same era.
“Deep Convolutional Networks on Graph-Structured Data”
Mikael Henaff, Joan Bruna and Yann LeCun · 2015
Cited alongside, same era.
“An Introduction to PYTHIA 8.2”
Torbjörn Sjöstrand, Stefan Ask, Jesper. Christiansen, Richard Corke, Nishita Desai, Philip Ilten, Stephen Mrenna, Stefan Prestel, Christine. Rasmussen and Peter. Skands · 2015
Cited alongside, same era.
“Group Equivariant Convolutional Networks”
Risi Kondor · 2018
Later among the works it cites.
“Clebsch-Gordan Nets: a Fully Fourier Space Spherical Convolutional Neural Network”
Risi Kondor, Zhen Lin and Shubhendu Trivedi · 2018
Later among the works it cites.
“On the Generalization of Equivariance and Convolution in Neural Networks to the Action of Compact Groups”
Risi Kondor and Shubhendu Trivedi · 2018
Later among the works it cites.
“Tensor Field Networks: Rotation- and Translation-Equivariant Neural Networks for 3D Point Clouds”
Nathaniel Thomas, Tess Smidt, Steven. Kearnes, Lusann Yang, Li Li, Kai Kohlhoff and Patrick Riley · 2018
Later among the works it cites.
“3D Steerable CNNs: Learning Rotationally Equivariant Features in Volumetric Data”
Maurice Weiler, Mario Geiger, Max Welling, Wouter Boomsma and Taco Cohen · 2018
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Taco Cohen and Max Welling · 2016
Cited alongside, same era.
“Boosted jet identification using particle candidates and deep neural networks”, 2017
CMS Collaboration · 2017
Cited alongside, same era.
“Geometric Deep Learning on Graphs and Manifolds Using Mixture Model CNNs”
Federico Monti, Davide Boscaini, Jonathan Masci, Emanuele Rodolà, Jan Svoboda and Michael. Bronstein · 2017
Cited alongside, same era.
“Jet Constituents for Deep Neural Network Based Top Quark Tagging”, 2017
Jannicke Pearkes, Wojciech Fedorko, Alison Lister and Colin Gay · 2017
Cited alongside, same era.
“Harmonic Networks: Deep Translation and Rotation Equivariance”
Daniel. Worrall, Stephan. Garbin, Daniyar Turmukhambetov and Gabriel. Brostow · 2017
Cited alongside, same era.
“Aggregated Residual Transformations for Deep Neural Networks”
Saining Xie, Ross. Girshick, Piotr Dollár, Zhuowen Tu and Kaiming He · 2017
Cited alongside, same era.
“Deep Sets”
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Russ Salakhutdinov and Alexander Smola · 2017
Cited alongside, same era.
Later among the works it cites.
“Universal approximations of invariant maps by neural networks”
Dmitry Yarotsky · 2018
Later among the works it cites.
“Cormorant: Covariant Molecular Neural Networks”
Brandon. Anderson, Truong-Son Hy and Risi Kondor · 2019
Later among the works it cites.
“The Machine Learning Landscape of Top Taggers”
Anja Butter · 2019
Later among the works it cites.
“A General Theory of Equivariant CNNs on Homogeneous Spaces”
Taco Cohen, Mario Geiger and Maurice Weiler · 2019
Later among the works it cites.
“Gauge Equivariant Convolutional Networks and the Icosahedral CNN”
Taco Cohen, Maurice Weiler, Berkay Kicanaoglu and Max Welling · 2019
Later among the works it cites.
“Lorentz Boost Networks: Autonomous Physics-Inspired Feature Engineering”
M. Erdmann, E. Geiser, Y. Rath and M. Rieger · 2019
Later among the works it cites.
“Top Quark Tagging Reference Dataset”, 2019
Gregor Kasieczka, Tilman Plehn, Jennifer Thompson and Michael Russel · 2019
Later among the works it cites.
“Energy Flow Networks: Deep Sets for Particle Jets”
Patrick. Komiske, Eric. Metodiev and Jesse Thaler · 2019
Later among the works it cites.
“Jet Substructure at the Large Hadron Collider: A Review of Recent Advances in Theory and Machine Learning”, 2017
Andrew. Larkoski, Ian Moult and Benjamin Nachman · 2019
Later among the works it cites.
“Jet tagging via particle clouds”
Huilin Qu and Loukas Gouskos · 2020
Closest in time.