Sandeep Madireddy

According to our database, Sandeep Madireddy authored at least 40 papers between 2017 and 2024.

Collaborative distances:

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

2024

Question Rephrasing for Quantifying Uncertainty in Large Language Models: Applications in Molecular Chemistry Tasks.

Zizhang Chen, Pengyu Hong, Sandeep Madireddy

CoRR, 2024

AstroMLab 1: Who Wins Astronomy Jeopardy!?

Yuan-Sen Ting, Tuan Dung Nguyen, Tirthankar Ghosal, Rui Pan, Hardik Arora, Zechang Sun, Tijmen de Haan, Nesar Ramachandra, Azton Wells, Sandeep Madireddy, Alberto Accomazzi

CoRR, 2024

Parametric Sensitivities of a Wind-driven Baroclinic Ocean Using Neural Surrogates.

Yixuan Sun, Elizabeth Cucuzzella, Steven Brus, Sri Hari Krishna Narayanan, Balasubramanya T. Nadiga, Luke Van Roekel, Jan Hückelheim, Sandeep Madireddy, Patrick Heimbach

Proceedings of the Platform for Advanced Scientific Computing Conference, 2024

REMEDI: Corrective Transformations for Improved Neural Entropy Estimation.

Viktor Nilsson, Anirban Samaddar, Sandeep Madireddy, Pierre Nyquist

Proceedings of the Forty-first International Conference on Machine Learning, 2024

2023

DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection.

Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild

Mach. Learn. Sci. Technol., June, 2023

A domain-agnostic approach for characterization of lifelong learning systems.

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

Neural Networks, March, 2023

Scaling transformer neural networks for skillful and reliable medium-range weather forecasting.

Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian T. Foster, Aditya Grover

CoRR, 2023

Surrogate Neural Networks to Estimate Parametric Sensitivity of Ocean Models.

Yixuan Sun, Elizabeth Cucuzzella, Steven Brus, Sri Hari Krishna Narayanan, Balu Nadiga, Luke Van Roekel, Jan Hückelheim, Sandeep Madireddy

CoRR, 2023

Towards Continually Learning Application Performance Models.

Ray A. O. Sinurat, Anurag Reddy Daram, Haryadi S. Gunawi, Robert B. Ross, Sandeep Madireddy

CoRR, 2023

Memristor-Spikelearn: A Spiking Neural Network Simulator for Studying Synaptic Plasticity under Realistic Device and Circuit Behaviors.

Yuming Liu, Angel Yanguas-Gil, Sandeep Madireddy, Yanjing Li

Proceedings of the Design, Automation & Test in Europe Conference & Exhibition, 2023

Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures.

Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash

Proceedings of the Conference on Lifelong Learning Agents, 2023

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck.

Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash, Taps Maiti, Gustavo de los Campos, Ian Fischer

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Biological underpinnings for lifelong learning machines.

Dhireesha Kudithipudi, Mario Aguilar-Simon, Jonathan Babb, Maxim Bazhenov, Douglas Blackiston, Josh C. Bongard, Andrew P. Brna, Suraj Chakravarthi Raja, Nick Cheney, Jeff Clune, Anurag Reddy Daram, Stefano Fusi, Peter Helfer, Leslie Kay, Nicholas Ketz, Zsolt Kira, Soheil Kolouri, Jeffrey L. Krichmar, Sam Kriegman, Michael Levin, Sandeep Madireddy, Santosh Manicka, Ali Marjaninejad, Bruce McNaughton, Risto Miikkulainen, Zaneta Navratilova, Tej Pandit, Alice Parker, Praveen K. Pilly, Sebastian Risi, Terrence J. Sejnowski, Andrea Soltoggio, Nicholas Soures, Andreas S. Tolias, Darío Urbina-Meléndez, Francisco J. Valero Cuevas, Gido M. van de Ven, Joshua T. Vogelstein, Felix Wang, Ron Weiss, Angel Yanguas-Gil, Xinyun Zou, Hava T. Siegelmann

Nat. Mach. Intell., 2022

DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification.

Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild

Mach. Learn. Sci. Technol., 2022

General policy mapping: online continual reinforcement learning inspired on the insect brain.

Angel Yanguas-Gil, Sandeep Madireddy

CoRR, 2022

Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection.

Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild

CoRR, 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

Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck.

Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash

CoRR, 2022

A Taxonomy of Error Sources in HPC I/O Machine Learning Models.

Mihailo Isakov, Mikaela Currier, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Glenn K. Lockwood, Michel A. Kinsy

Proceedings of the SC22: International Conference for High Performance Computing, 2022

AutoML for neuromorphic computing and application-driven co-design: asynchronous, massively parallel optimization of spiking architectures.

Angel Yanguas-Gil, Sandeep Madireddy

Proceedings of the IEEE International Conference on Rebooting Computing, 2022

HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization.

Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross

Proceedings of the IEEE International Conference on Cluster Computing, 2022

2021

In situ compression artifact removal in scientific data using deep transfer learning and experience replay.

Sandeep Madireddy, Ji Hwan Park, Sunwoo Lee, Prasanna Balaprakash, Shinjae Yoo, Wei-keng Liao, Cory D. Hauck, M. Paul Laiu, Richard Archibald

Mach. Learn. Sci. Technol., 2021

Robustness of deep learning algorithms in astronomy - galaxy morphology studies.

Aleksandra Ciprijanovic, Diana Kafkes, Gabriel N. Perdue, Kevin Pedro, Gregory F. Snyder, F. Javier Sánchez, Sandeep Madireddy, Stefan M. Wild, Brian Nord

CoRR, 2021

Applications and Techniques for Fast Machine Learning in Science.

Allison McCarn Deiana, Nhan Tran, Joshua Agar, Michaela Blott, Giuseppe Di Guglielmo, Javier M. Duarte, Philip C. Harris, Scott Hauck, Mia Liu, Mark S. Neubauer, Jennifer Ngadiuba, Seda Ogrenci Memik, Maurizio Pierini, Thea Aarrestad, Steffen Bähr, Jürgen Becker, Anne-Sophie Berthold, Richard J. Bonventre, Tomás E. Müller-Bravo, Markus Diefenthaler, Zhen Dong, Nick Fritzsche, Amir Gholami, Ekaterina Govorkova, Kyle J. Hazelwood, Christian Herwig, Babar Khan, Sehoon Kim, Thomas Klijnsma, Yaling Liu, Kin Ho Lo, Tri Nguyen, Gianantonio Pezzullo, Seyedramin Rasoulinezhad, Ryan A. Rivera, Kate Scholberg, Justin Selig, Sougata Sen, Dmitri Strukov, William Tang, Savannah Thais, Kai Lukas Unger, Ricardo Vilalta, Belinavon Krosigk, Thomas K. Warburton, Maria Acosta Flechas, Anthony Aportela, Thomas Calvet, Leonardo Cristella, Daniel Diaz, Caterina Doglioni, Maria Domenica Galati, Elham E Khoda, Farah Fahim, Davide Giri, Benjamin Hawks, Duc Hoang, Burt Holzman, Shih-Chieh Hsu, Sergo Jindariani, Iris Johnson, Raghav Kansal, Ryan Kastner, Erik Katsavounidis, Jeffrey D. Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric A. Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan S. Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng

CoRR, 2021

DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains.

Aleksandra Ciprijanovic, Diana Kafkes, K. Downey, S. Jenkins, Gabriel N. Perdue, Sandeep Madireddy, T. Johnston, Gregory F. Snyder, Brian Nord

CoRR, 2021

2020

Domain adaptation techniques for improved cross-domain study of galaxy mergers.

Aleksandra Ciprijanovic, Diana Kafkes, S. Jenkins, K. Downey, Gabriel N. Perdue, Sandeep Madireddy, T. Johnston, Brian Nord

CoRR, 2020

Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning.

Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash

CoRR, 2020

Gauge: An Interactive Data-Driven Visualization Tool for HPC Application I/O Performance Analysis.

Eliakin Del Rosario, Mikaela Currier, Mihailo Isakov, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Kevin Harms, Shane Snyder, Michel A. Kinsy

Proceedings of the Fifth IEEE/ACM International Parallel Data Systems Workshop, 2020

HPC I/O throughput bottleneck analysis with explainable local models.

Mihailo Isakov, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Michel A. Kinsy

Proceedings of the International Conference for High Performance Computing, 2020

Toward Generalizable Models of I/O Throughput.

Mihailo Isakov, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Michel A. Kinsy

Proceedings of the 2020 IEEE/ACM International Workshop on Runtime and Operating Systems for Supercomputers, 2020

2019

Value-Added Chemical Discovery Using Reinforcement Learning.

Peihong Jiang, Hieu Doan, Sandeep Madireddy, Rajeev Surendran Assary, Prasanna Balaprakash

CoRR, 2019

Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images.

Sandeep Madireddy, Nan Li, Nesar Ramachandra, Prasanna Balaprakash, Salman Habib

CoRR, 2019

Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models.

Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash

CoRR, 2019

Adaptive Learning for Concept Drift in Application Performance Modeling.

Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Glenn K. Lockwood, Robert B. Ross, Shane Snyder, Stefan M. Wild

Proceedings of the 48th International Conference on Parallel Processing, 2019

Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning.

Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash

Proceedings of the International Conference on Neuromorphic Systems, 2019

Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time.

Sunwoo Lee, Qiao Kang, Sandeep Madireddy, Prasanna Balaprakash, Ankit Agrawal, Alok N. Choudhary, Richard Archibald, Wei-keng Liao

Proceedings of the 2019 IEEE International Conference on Big Data (IEEE BigData), 2019

2018

Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems.

Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild

Proceedings of the High Performance Computing - 33rd International Conference, 2018

Modeling I/O Performance Variability Using Conditional Variational Autoencoders.

Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild

Proceedings of the IEEE International Conference on Cluster Computing, 2018

2017

Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity.

Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild

Proceedings of the 2017 International Conference on Networking, Architecture, and Storage, 2017