Akshay Iyer

11 papers A* 1Journal 10

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing. AAAI Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi
2024	J	`jnl`	Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing. CoRR Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi
2023	J	`jnl`	Fully Bayesian Inference for Latent Variable Gaussian Process Models. SIAM/ASA J. Uncertain. Quantification Suraj Yerramilli, Akshay Iyer, Wei Chen, Daniel W. Apley
2022	J	`jnl`	An Automated System for Detecting Visual Damages of Wind Turbine Blades. CoRR Linh Nguyen, Akshay Iyer, Shweta Khushu
2022	J	`jnl`	Fully Bayesian inference for latent variable Gaussian process models. CoRR Suraj Yerramilli, Akshay Iyer, Wei Chen, Daniel W. Apley
2022	J	`jnl`	Learning to estimate a surrogate respiratory signal from cardiac motion by signal-to-signal translation. CoRR Akshay Iyer, Clifford Lindsay, P. Hendrik Pretorius, Michael A. King
2022	J	`jnl`	Learning to identify cracks on wind turbine blade surfaces using drone-based inspection images. CoRR Akshay Iyer, Linh Nguyen, Shweta Khushu
2022	J	`jnl`	Uncertainty-aware Mixed-variable Machine Learning for Materials Design. CoRR Hengrui Zhang, Wei Wayne Chen, Akshay Iyer, Daniel W. Apley, Wei Chen
2021	J	`jnl`	Scalable Gaussian Processes for Data-Driven Design using Big Data with Categorical Factors. CoRR Liwei Wang, Suraj Yerramilli, Akshay Iyer, Daniel W. Apley, Ping Zhu, Wei Chen
2019	J	`jnl`	A Conditional Generative Model for Predicting Material Microstructures from Processing Methods. CoRR Akshay Iyer, Biswadip Dey, Arindam Dasgupta, Wei Chen, Amit Chakraborty
2019	J	`jnl`	Data-Centric Mixed-Variable Bayesian Optimization For Materials Design. CoRR Akshay Iyer, Yichi Zhang, Aditya Prasad, Siyu Tao, Yixing Wang, Linda Schadler, L. Catherine Brinson, Wei Chen