78 citations · 124 across the 4 of their papers we have counts for
4 papers
Encoding Invariances in Deep Generative Models
Viraj Shah, Ameya Joshi, Sambuddha Ghosal +4
Reliable training of generative adversarial networks (GANs) typically require massive datasets in order to model complicated distributions. However, in several applications, traini…
Interpretable deep learning for guided structure-property explorations in photovoltaics
Balaji Sesha Sarath Pokuri, Sambuddha Ghosal, Apurva Kokate +2
The performance of an organic photovoltaic device is intricately connected to its active layer morphology. This connection between the active layer and device performance is very e…
Physics-aware Deep Generative Models for Creating Synthetic Microstructures
Rahul Singh, Viraj Shah, Balaji Pokuri +3
A key problem in computational material science deals with understanding the effect of material distribution (i.e., microstructure) on material performance. The challenge is to syn…
PARyOpt: A software for Parallel Asynchronous Remote Bayesian Optimization
Balaji Sesha Sarath Pokuri, Alec Lofquist, Chad M Risko +1
PARyOpt is a python based implementation of the Bayesian optimization routine designed for remote and asynchronous function evaluations. Bayesian optimization is especially attract…