Nathan M. Urban

30 papers A* 1A 1Misc 1Journal 20Unranked 7

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	C-LoRA: Contextual Low-Rank Adaptation for Uncertainty Estimation in Large Language Models. CoRR Amir Hossein Rahmati, Sanket R. Jantre, Weifeng Zhang, Yucheng Wang, Byung-Jun Yoon, Nathan M. Urban, Xiaoning Qian
2025	J	`jnl`	ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation. J. Mach. Learn. Res. Sungduk Yu, Zeyuan Hu, Akshay Subramaniam, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius J. M. Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Helge Heuer, Benjamin R. Hillman, Andrea M. Jenney, Nana Liu, Alistair White, Tian Zheng, Zhiming Kuang, Fiaz Ahmed, Elizabeth A. Barnes, Noah D. Brenowitz, Christopher S. Bretherton, Veronika Eyring, Savannah L. Ferretti, Nicholas J. Lutsko, Pierre Gentine, Stephan Mandt, J. David Neelin, Rose Yu, Laure Zanna, Nathan M. Urban, Janni Yuval, Ryan Abernathey, Pierre Baldi, Wayne Chuang, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Po-Lun Ma, Sara Shamekh, Guang Zhang, Michael S. Pritchard
2025	J	`jnl`	Cost-effective Reduced-Order Modeling via Bayesian Active Learning. CoRR Amir Hossein Rahmati, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian
2025	J	`jnl`	Data-Augmented Few-Shot Neural Stencil Emulation for System Identification of Computer Models. CoRR Sanket R. Jantre, Deepak Akhare, Xiaoning Qian, Nathan M. Urban
2025	J	`jnl`	Robust, Online, and Adaptive Decentralized Gaussian Processes. CoRR Fernando Llorente, Daniel Waxman, Sanket R. Jantre, Nathan M. Urban, Susan E. Minkoff
2025	J	`jnl`	Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis. CoRR Sanket R. Jantre, Tianle Wang, Gilchan Park, Kriti Chopra, Nicholas Jeon, Xiaoning Qian, Nathan M. Urban, Byung-Jun Yoon
2024	J	`jnl`	Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders. CoRR A. N. M. Nafiz Abeer, Sanket R. Jantre, Nathan M. Urban, Byung-Jun Yoon
2024	—	`conf`	Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data. MLSP Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
2024	J	`jnl`	Implicit Neural Representations for Simultaneous Reduction and Continuous Reconstruction of Multi-Altitude Climate Data. CoRR Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
2024	Misc	`conf`	Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks. ICASSP Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
2024	—	`conf`	Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design. MLSP A. N. M. Nafiz Abeer, Sanket R. Jantre, Nathan M. Urban, Byung-Jun Yoon
2024	J	`jnl`	Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design. CoRR A. N. M. Nafiz Abeer, Sanket R. Jantre, Nathan M. Urban, Byung-Jun Yoon
2024	A	`conf`	Multi-fidelity Bayesian Optimization with Multiple Information Sources of Input-dependent Fidelity. UAI Mingzhou Fan, Byung-Jun Yoon, Edward R. Dougherty, Nathan M. Urban, Francis J. Alexander, Raymundo Arróyave, Xiaoning Qian
2024	J	`jnl`	Multi-modal Representation Learning for Cross-modal Prediction of Continuous Weather Patterns from Discrete Low-Dimensional Data. CoRR Alif Bin Abdul Qayyum, Xihaier Luo, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
2024	J	`jnl`	Multi-objective latent space optimization of generative molecular design models. Patterns A. N. M. Nafiz Abeer, Nathan M. Urban, M. Ryan Weil, Francis J. Alexander, Byung-Jun Yoon
2024	J	`jnl`	Pathway-Guided Optimization of Deep Generative Molecular Design Models for Cancer Therapy. CoRR Alif Bin Abdul Qayyum, Susan D. Mertins, Amanda K. Paulson, Nathan M. Urban, Byung-Jun Yoon
2024	J	`jnl`	Understanding Uncertainty-based Active Learning Under Model Mismatch. CoRR Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian
2024	—	`conf`	When Uncertainty-Based Active Learning May Fail? ICPR (1) Amir Hossein Rahmati, Mingzhou Fan, Ruida Zhou, Nathan M. Urban, Byung-Jun Yoon, Xiaoning Qian
2023	A*	`conf`	ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation. NeurIPS Sungduk Yu, Walter M. Hannah, Liran Peng, Jerry Lin, Mohamed Aziz Bhouri, Ritwik Gupta, Björn Lütjens, Justus C. Will, Gunnar Behrens, Julius Busecke, Nora Loose, Charles Stern, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Animashree Anandkumar, Noah D. Brenowitz, Veronika Eyring, Nicholas Geneva, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Akshay Subramaniam, Carl Vondrick, Rose Yu, Laure Zanna, Tian Zheng, Ryan Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Christopher S. Bretherton, Peter M. Caldwell, Wayne Chuang, Yilun Han, Yu Huang, Fernando Iglesias-Suarez, Sanket R. Jantre, Karthik Kashinath, Marat Khairoutdinov, Thorsten Kurth, Nicholas J. Lutsko, Po-Lun Ma, Griffin Mooers, J. David Neelin, David A. Randall, Sara Shamekh, Mark Taylor, Nathan M. Urban, Janni Yuval, Guang Zhang, Mike Pritchard
2023	J	`jnl`	Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks. CoRR Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon
2022	J	`jnl`	Multi-Objective Latent Space Optimization of Generative Molecular Design Models. CoRR A. N. M. Nafiz Abeer, Nathan M. Urban, M. Ryan Weil, Francis J. Alexander, Byung-Jun Yoon
2021	J	`jnl`	Differentiable programming for online training of a neural artificial viscosity function within a staggered grid Lagrangian hydrodynamics scheme. Mach. Learn. Sci. Technol. Pake Melland, Jason Albright, Nathan M. Urban
2021	—	`conf`	Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks. IEEE BigData Divya Banesh, Nishant Panda, Ayan Biswas, Luke Van Roekel, Diane Oyen, Nathan M. Urban, Michael Grosskopf, Jonathan David Wolfe, Earl Lawrence
2021	—	`conf`	In Situ Climate Modeling for Analyzing Extreme Weather Events. ISAV@SC Soumya Dutta, Natalie Klein, Li Tang, Jonathan David Wolfe, Luke Van Roekel, James Joseph Benedict, Ayan Biswas, Earl Lawrence, Nathan M. Urban
2021	—	`conf`	In-Situ Spatial Inference on Climate Simulations with Sparse Gaussian Processes. ISAV@SC Michael Grosskopf, Earl Lawrence, Ayan Biswas, Li Tang, Kelin Rumsey, Luke Van Roekel, Nathan M. Urban
2020	—	`conf`	Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data. IEEE VIS (Short Papers) Subhashis Hazarika, Ayan Biswas, Phillip J. Wolfram, Earl Lawrence, Nathan M. Urban
2020	J	`jnl`	Relationship-aware Multivariate Sampling Strategy for Scientific Simulation Data. CoRR Subhashis Hazarika, Ayan Biswas, Phillip J. Wolfram, Earl Lawrence, Nathan M. Urban
2019	J	`jnl`	Scalable Extended Dynamic Mode Decomposition Using Random Kernel Approximation. SIAM J. Sci. Comput. Anthony M. DeGennaro, Nathan M. Urban
2013	J	`jnl`	Multivariate Gaussian Process Emulators With Nonseparable Covariance Structures. Technometrics Thomas E. Fricker, Jeremy E. Oakley, Nathan M. Urban
2010	J	`jnl`	A comparison of Latin hypercube and grid ensemble designs for the multivariate emulation of an Earth system model. Comput. Geosci. Nathan M. Urban, Thomas E. Fricker