2 citations · 3 across the 6 of their papers we have counts for
Showing 2022Show all
3 papers · 1 filter
cs.LG2022
Designing with Non-Finite Output Dimension via Fourier Coefficients of Neural Waveforms
Jonathan S. Kent
Ordinary Deep Learning models require having the dimension of their outputs determined by a human practitioner prior to training and operation. For design tasks, this places a hard…
cs.LG2022
Chaos Theory and Adversarial Robustness
Jonathan S. Kent
Neural networks, being susceptible to adversarial attacks, should face a strict level of scrutiny before being deployed in critical or adversarial applications. This paper uses ide…
cs.LG2022★ 1 cited
Indecision Trees: Learning Argument-Based Reasoning under Quantified Uncertainty
Jonathan S. Kent, David H. Menager
Using Machine Learning systems in the real world can often be problematic, with inexplicable black-box models, the assumed certainty of imperfect measurements, or providing a singl…