4 citations · 7 across the 4 of their papers we have counts for
4 papers
ChemGymRL: An Interactive Framework for Reinforcement Learning for Digital Chemistry
Chris Beeler, Sriram Ganapathi Subramanian, Kyle Sprague +10
This paper provides a simulated laboratory for making use of Reinforcement Learning (RL) for chemical discovery. Since RL is fairly data intensive, training agents `on-the-fly' by…
Reinforcement Learning-based Wavefront Sensorless Adaptive Optics Approaches for Satellite-to-Ground Laser Communication
Payam Parvizi, Runnan Zou, Colin Bellinger +2
Optical satellite-to-ground communication (OSGC) has the potential to improve access to fast and affordable Internet in remote regions. Atmospheric turbulence, however, distorts th…
Efficient Augmentation for Imbalanced Deep Learning
Damien Dablain, Colin Bellinger, Bartosz Krawczyk +1
Deep learning models tend to memorize training data, which hurts their ability to generalize to under-represented classes. We empirically study a convolutional neural network's int…
Scientific Discovery and the Cost of Measurement -- Balancing Information and Cost in Reinforcement Learning
Colin Bellinger, Andriy Drozdyuk, Mark Crowley +1
The use of reinforcement learning (RL) in scientific applications, such as materials design and automated chemistry, is increasing. A major challenge, however, lies in fact that me…