1 citations · 1 across the 1 of their papers we have counts for
4 papers
Learning in the Machine: the Symmetries of the Deep Learning Channel
Pierre Baldi, Peter Sadowski, Zhiqin Lu
In a physical neural system, learning rules must be local both in space and time. In order for learning to occur, non-local information must be communicated to the deep synapses th…
Efficient Antihydrogen Detection in Antimatter Physics by Deep Learning
Peter Sadowski, Balint Radics, Ananya +2
Antihydrogen is at the forefront of antimatter research at the CERN Antiproton Decelerator. Experiments aiming to test the fundamental CPT symmetry and antigravity effects require…
Theano: A Python framework for fast computation of mathematical expressions
The Theano Development Team, Rami Al-Rfou, Guillaume Alain +110
Theano is a Python library that allows to define, optimize, and evaluate mathematical expressions involving multi-dimensional arrays efficiently. Since its introduction, it has bee…
Jet Substructure Classification in High-Energy Physics with Deep Neural Networks
Pierre Baldi, Kevin Bauer, Clara Eng +2
At the extreme energies of the Large Hadron Collider, massive particles can be produced at such high velocities that their hadronic decays are collimated and the resulting jets ove…