15 citations · 21 across the 6 of their papers we have counts for
4 papers · 1 filter
JORLDY: a fully customizable open source framework for reinforcement learning
Kyushik Min, Hyunho Lee, Kwansu Shin +4
Recently, Reinforcement Learning (RL) has been actively researched in both academic and industrial fields. However, there exist only a few RL frameworks which are developed for res…
Safe Predictors for Enforcing Input-Output Specifications
Stephen Mell, Olivia Brown, Justin Goodwin +1
We present an approach for designing correct-by-construction neural networks (and other machine learning models) that are guaranteed to be consistent with a collection of input-out…
Optimization Methods for Interpretable Differentiable Decision Trees in Reinforcement Learning
Andrew Silva, Taylor Killian, Ivan Dario Jimenez Rodriguez +2
Decision trees are ubiquitous in machine learning for their ease of use and interpretability. Yet, these models are not typically employed in reinforcement learning as they cannot…
Learning Robust Representations for Automatic Target Recognition
Justin A. Goodwin, Olivia M. Brown, Taylor W. Killian +1
Radio frequency (RF) sensors are used alongside other sensing modalities to provide rich representations of the world. Given the high variability of complex-valued target responses…