Data-Centric Mixed-Variable Bayesian Optimization For Materials Design. - Akshay Iyer; Yichi Zhang; Aditya Prasad; Siyu Tao 003; Yixing Wang; Linda Schadler; L. Catherine Brinson; Wei Chen 041 (CoRR, 2019)

A Conditional Generative Model for Predicting Material Microstructures from Processing Methods. - Akshay Iyer; Biswadip Dey; Arindam Dasgupta; Wei Chen 041; Amit Chakraborty (CoRR, 2019)

Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors. - Liwei Wang; Suraj Yerramilli; Akshay Iyer; Daniel W. Apley; Ping Zhu 006; Wei Chen 041 (CoRR, 2021)

An Automated System for Detecting Visual Damages of Wind Turbine Blades. - Linh Nguyen; Akshay Iyer; Shweta Khushu (CoRR, 2022)

Uncertainty-aware Mixed-variable Machine Learning for Materials Design. - Hengrui Zhang; Wei Wayne Chen; Akshay Iyer; Daniel W. Apley; Wei Chen 041 (CoRR, 2022)

Learning to identify cracks on wind turbine blade surfaces using drone-based inspection images. - Akshay Iyer; Linh Nguyen; Shweta Khushu (CoRR, 2022)

Learning to estimate a surrogate respiratory signal from cardiac motion by signal-to-signal translation. - Akshay Iyer; Clifford Lindsay; P. Hendrik Pretorius; Michael A. King (CoRR, 2022)

Fully Bayesian Inference for Latent Variable Gaussian Process Models. - Suraj Yerramilli; Akshay Iyer; Wei Chen 041; Daniel W. Apley (SIAM/ASA J. Uncertain. Quantification, 2023)

Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing. - Lokesh Nagalapatti; Akshay Iyer; Abir De; Sunita Sarawagi (AAAI, 2024)