Sanket R. Jantre

19 papers A* 1B 1Misc 1Journal 15Unranked 1

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`	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`	Spike-and-Slab Shrinkage Priors for Structurally Sparse Bayesian Neural Networks. IEEE Trans. Neural Networks Learn. Syst. Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti
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	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
2023	J	`jnl`	A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks. CoRR Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti
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`	ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators. CoRR Sungduk Yu, Walter M. Hannah, Liran Peng, Mohamed Aziz Bhouri, Ritwik Gupta, Jerry Lin, Björn Lütjens, Justus C. Will, Tom Beucler, Bryce E. Harrop, Benjamin R. Hillman, Andrea M. Jenney, Savannah L. Ferretti, Nana Liu, Anima Anandkumar, Noah D. Brenowitz, Veronika Eyring, Pierre Gentine, Stephan Mandt, Jaideep Pathak, Carl Vondrick, Rose Yu, Laure Zanna, Ryan P. Abernathey, Fiaz Ahmed, David C. Bader, Pierre Baldi, Elizabeth A. Barnes, Gunnar Behrens, Christopher S. Bretherton, Julius J. M. Busecke, 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, Akshay Subramaniam, Mark A. Taylor, et al.
2023	J	`jnl`	Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details. Neural Networks Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti
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`	Sequential Bayesian Neural Subnetwork Ensembles. CoRR Sanket R. Jantre, Sandeep Madireddy, Shrijita Bhattacharya, Tapabrata Maiti, Prasanna Balaprakash
2022	J	`jnl`	Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness. CoRR Sumegha Premchandar, Sandeep Madireddy, Sanket R. Jantre, Prasanna Balaprakash
2021	J	`jnl`	Layer Adaptive Node Selection in Bayesian Neural Networks: Statistical Guarantees and Implementation Details. CoRR Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti
2021	B	`conf`	Low-Rank Tensor Regression for X-Ray Tomography. ICIP Sanket R. Jantre, Zichao Wendy Di