Sanket R. Jantre

According to our database, Sanket R. Jantre authored at least 10 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Enhancing Generative Molecular Design via Uncertainty-guided Fine-tuning of Variational Autoencoders.

A. N. M. Nafiz Abeer, Sanket R. Jantre, Nathan M. Urban, Byung-Jun Yoon

CoRR, 2024

Leveraging Active Subspaces to Capture Epistemic Model Uncertainty in Deep Generative Models for Molecular Design.

A. N. M. Nafiz Abeer, Sanket R. Jantre, Nathan M. Urban, Byung-Jun Yoon

Proceedings of the 34th IEEE International Workshop on Machine Learning for Signal Processing, 2024

Learning Active Subspaces for Effective and Scalable Uncertainty Quantification in Deep Neural Networks.

Sanket R. Jantre, Nathan M. Urban, Xiaoning Qian, Byung-Jun Yoon

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Layer adaptive node selection in Bayesian neural networks: Statistical guarantees and implementation details.

Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti

Neural Networks, October, 2023

A comprehensive study of spike and slab shrinkage priors for structurally sparse Bayesian neural networks.

Sanket R. Jantre, Shrijita Bhattacharya, Tapabrata Maiti

CoRR, 2023

ClimSim: An open large-scale dataset for training high-resolution physics emulators in hybrid multi-scale climate simulators.

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.

CoRR, 2023

ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation.

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

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness.

Sumegha Premchandar, Sandeep Madireddy, Sanket R. Jantre, Prasanna Balaprakash

CoRR, 2022

Sequential Bayesian Neural Subnetwork Ensembles.

Sanket R. Jantre, Sandeep Madireddy, Shrijita Bhattacharya, Tapabrata Maiti, Prasanna Balaprakash

CoRR, 2022

2021

Low-Rank Tensor Regression for X-Ray Tomography.

Sanket R. Jantre, Zichao Wendy Di

Proceedings of the 2021 IEEE International Conference on Image Processing, 2021