159 citations · 306 across the 5 of their papers we have counts for
6 papers
Orbital Graph Convolutional Neural Network for Material Property Prediction
Mohammadreza Karamad, Rishikesh Magar, Yuting Shi +3
Material representations that are compatible with machine learning models play a key role in developing models that exhibit high accuracy for property prediction. Atomic orbital in…
Reduced Thermal Conductivity of Supported and Encased Monolayer and Bilayer MoS
Alexander J. Gabourie, Saurabh V. Suryavanshi, Amir Barati Farimani +1
Electrical and thermal properties of atomically thin two-dimensional (2D) materials are affected by their environment, e.g. through remote phonon scattering or dielectric screening…
Potential Neutralizing Antibodies Discovered for Novel Corona Virus Using Machine Learning
Rishikesh Magar, Prakarsh Yadav, Amir Barati Farimani
The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. Recent outbreak of novel coronavirus infect…
Effects of sparse rewards of different magnitudes in the speed of learning of model-based actor critic methods
Juan Vargas, Lazar Andjelic, Amir Barati Farimani
Actor critic methods with sparse rewards in model-based deep reinforcement learning typically require a deterministic binary reward function that reflects only two possible outcome…
Creativity in Robot Manipulation with Deep Reinforcement Learning
Juan Carlos Vargas, Malhar Bhoite, Amir Barati Farimani
Deep Reinforcement Learning (DRL) has emerged as a powerful control technique in robotic science. In contrast to control theory, DRL is more robust in the thorough exploration of t…
Deep Learning the Physics of Transport Phenomena
Amir Barati Farimani, Joseph Gomes, Vijay S. Pande
We have developed a new data-driven paradigm for the rapid inference, modeling and simulation of the physics of transport phenomena by deep learning. Using conditional generative a…