366 citations · 373 across the 5 of their papers we have counts for
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cs.AI2019
Questions to Guide the Future of Artificial Intelligence Research
Jordan Ott
The field of machine learning has focused, primarily, on discretized sub-problems (i.e. vision, speech, natural language) of intelligence. While neuroscience tends to be observatio…
cs.LG2019
Learning in the Machine: To Share or Not to Share?
Jordan Ott, Erik Linstead, Nicholas LaHaye +1
Weight-sharing is one of the pillars behind Convolutional Neural Networks and their successes. However, in physical neural systems such as the brain, weight-sharing is implausible.…
physics.comp-ph2019
Enforcing Analytic Constraints in Neural-Networks Emulating Physical Systems
Tom Beucler, Michael Pritchard, Stephan Rasp +3
Neural networks can emulate nonlinear physical systems with high accuracy, yet they may produce physically-inconsistent results when violating fundamental constraints. Here, we int…