70 citations · 117 across the 11 of their papers we have counts for
3 papers · 1 filter
PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics
Alexander Bogatskiy, Timothy Hoffman, David W. Miller +1
Many current approaches to machine learning in particle physics use generic architectures that require large numbers of parameters and disregard underlying physics principles, limi…
Innovations in trigger and data acquisition systems for next-generation physics facilities
Rainer Bartoldus, Catrin Bernius, David W. Miller
Data-intensive physics facilities are increasingly reliant on heterogeneous and large-scale data processing and computational systems in order to collect, distribute, process, filt…
Symmetry Group Equivariant Architectures for Physics
Alexander Bogatskiy, Sanmay Ganguly, Thomas Kipf +8
Physical theories grounded in mathematical symmetries are an essential component of our understanding of a wide range of properties of the universe. Similarly, in the domain of mac…