Thomas Yong-Jin Han

14 papers A* 1A 1Journal 11Unranked 1

Year	Rank	Type	Title / Venue / Authors
2021	A	`conf`	Deep kernels with probabilistic embeddings for small-data learning. UAI Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han
2021	J	`jnl`	MR-GAN: Manifold Regularized Generative Adversarial Networks for Scientific Data. SIAM J. Math. Data Sci. Qunwei Li, Bhavya Kailkhura, Rushil Anirudh, Jize Zhang, Yi Zhou, Yingbin Liang, Thomas Yong-Jin Han, Pramod K. Varshney
2021	J	`jnl`	Predicting Energetics Materials' Crystalline Density from Chemical Structure by Machine Learning. J. Chem. Inf. Model. Phan Nguyen, Donald Loveland, Joanne Taery Kim, Piyush Karande, Anna M. Hiszpanski, Thomas Yong-Jin Han
2020	J	`jnl`	Actionable Attribution Maps for Scientific Machine Learning. CoRR Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han
2020	J	`jnl`	Automated Identification of Molecular Crystals' Packing Motifs. J. Chem. Inf. Model. Donald Loveland, Bhavya Kailkhura, Piyush Karande, Anna M. Hiszpanski, Thomas Yong-Jin Han
2020	J	`jnl`	Explainable Deep Learning for Uncovering Actionable Scientific Insights for Materials Discovery and Design. CoRR Shusen Liu, Bhavya Kailkhura, Jize Zhang, Anna M. Hiszpanski, Emily Robertson, Donald Loveland, Thomas Yong-Jin Han
2020	J	`jnl`	Leveraging Uncertainty from Deep Learning for Trustworthy Materials Discovery Workflows. CoRR Jize Zhang, Bhavya Kailkhura, Thomas Yong-Jin Han
2020	A*	`conf`	Mix-n-Match : Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning. ICML Jize Zhang, Bhavya Kailkhura, Thomas Yong-Jin Han
2020	J	`jnl`	Mix-n-Match: Ensemble and Compositional Methods for Uncertainty Calibration in Deep Learning. CoRR Jize Zhang, Bhavya Kailkhura, Thomas Yong-Jin Han
2020	J	`jnl`	Nanomaterial Synthesis Insights from Machine Learning of Scientific Articles by Extracting, Structuring, and Visualizing Knowledge. J. Chem. Inf. Model. Anna M. Hiszpanski, Brian Gallagher, Karthik Chellappan, Peggy Li, Shusen Liu, Hyojin Kim, Jinkyu Han, Bhavya Kailkhura, David J. Buttler, Thomas Yong-Jin Han
2020	J	`jnl`	Probabilistic Neighbourhood Component Analysis: Sample Efficient Uncertainty Estimation in Deep Learning. CoRR Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han
2019	J	`jnl`	Deep Probabilistic Kernels for Sample-Efficient Learning. CoRR Ankur Mallick, Chaitanya Dwivedi, Bhavya Kailkhura, Gauri Joshi, Thomas Yong-Jin Han
2019	—	`conf`	Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. OST@ICDAR Huichen Yang, Alice Lam, Thomas Yong-Jin Han, David Buttler, William H. Hsu, Carlos A. Aguirre, Maria F. De La Torre, Derek Christensen, Luis Bobadilla, Emily Davich, Jordan Roth, Lei Luo, Yihong Theis
2019	J	`jnl`	Pipelines for Procedural Information Extraction from Scientific Literature: Towards Recipes using Machine Learning and Data Science. CoRR Huichen Yang, Carlos A. Aguirre, Maria F. De La Torre, Derek Christensen, Luis Bobadilla, Emily Davich, Jordan Roth, Lei Luo, Yihong Theis, Alice Lam, Thomas Yong-Jin Han, David Buttler, William H. Hsu