Sandeep Madireddy

Publication Activity (10 Years)

Years Active: 2017-2024
Publications (10 Years): 47

Top Topics

Machine Learning Models

Weather Forecasting

Domain Adaptation

Top Venues

Mach. Learn. Sci. Technol.

Publications

Yixuan Sun, Elizabeth Cucuzzella, Steven Brus, Sri Hari Krishna Narayanan, Balasubramanya T. Nadiga, Luke Van Roekel, Jan Hückelheim, Sandeep Madireddy, Patrick Heimbach
Parametric Sensitivities of a Wind-driven Baroclinic Ocean Using Neural Surrogates. PASC (2024)
Viktor Nilsson, Anirban Samaddar, Sandeep Madireddy, Pierre Nyquist
REMEDI: Corrective Transformations for Improved Neural Entropy Estimation. CoRR (2024)
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
AstroMLab 1: Who Wins Astronomy Jeopardy!? CoRR (2024)
Ray A. O. Sinurat, Anurag Reddy Daram, Haryadi S. Gunawi, Robert B. Ross, Sandeep Madireddy
Towards Continually Learning Application Performance Models. CoRR (2023)
Angel Yanguas-Gil, Sandeep Madireddy
AutoML for neuromorphic computing and application-driven co-design: asynchronous, massively parallel optimization of spiking architectures. CoRR (2023)
Yixuan Sun, Elizabeth Cucuzzella, Steven Brus, Sri Hari Krishna Narayanan, Balu Nadiga, Luke Van Roekel, Jan Hückelheim, Sandeep Madireddy
Surrogate Neural Networks to Estimate Parametric Sensitivity of Ocean Models. CoRR (2023)
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 Dimitri Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael L. 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
A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems. CoRR (2023)
Yuming Liu, Angel Yanguas-Gil, Sandeep Madireddy, Yanjing Li
Memristor-Spikelearn: A Spiking Neural Network Simulator for Studying Synaptic Plasticity under Realistic Device and Circuit Behaviors. DATE (2023)
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 L. 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
A domain-agnostic approach for characterization of lifelong learning systems. Neural Networks 160 (2023)
Tung Nguyen, Rohan Shah, Hritik Bansal, Troy Arcomano, Sandeep Madireddy, Romit Maulik, Veerabhadra Kotamarthi, Ian T. Foster, Aditya Grover
Scaling transformer neural networks for skillful and reliable medium-range weather forecasting. CoRR (2023)
Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash, Taps Maiti, Gustavo de los Campos, Ian Fischer
Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck. AISTATS (2023)
Aleksandra Ciprijanovic, A. Lewis, K. Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
DeepAstroUDA: Semi-Supervised Universal Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR (2023)
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures. CoRR (2023)
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
Improving Performance in Continual Learning Tasks using Bio-Inspired Architectures. CoLLAs (2023)
Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
DeepAstroUDA: semi-supervised universal domain adaptation for cross-survey galaxy morphology classification and anomaly detection. Mach. Learn. Sci. Technol. 4 (2) (2023)
Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross
HPC Storage Service Autotuning Using Variational- Autoencoder -Guided Asynchronous Bayesian Optimization. CLUSTER (2022)
Mihailo Isakov, Mikaela Currier, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Glenn K. Lockwood, Michel A. Kinsy
A Taxonomy of Error Sources in HPC I/O Machine Learning Models. SC (2022)
Angel Yanguas-Gil, Sandeep Madireddy
General policy mapping: online continual reinforcement learning inspired on the insect brain. CoRR (2022)
Angel Yanguas-Gil, Sandeep Madireddy
AutoML for neuromorphic computing and application-driven co-design: asynchronous, massively parallel optimization of spiking architectures. ICRC (2022)
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
Biological underpinnings for lifelong learning machines. Nat. Mach. Intell. 4 (3) (2022)
Anirban Samaddar, Sandeep Madireddy, Prasanna Balaprakash
Sparsity-Inducing Categorical Prior Improves Robustness of the Information Bottleneck. CoRR (2022)
Sanket Jantre, Sandeep Madireddy, Shrijita Bhattacharya, Tapabrata Maiti, Prasanna Balaprakash
Sequential Bayesian Neural Subnetwork Ensembles. CoRR (2022)
Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
DeepAdversaries: examining the robustness of deep learning models for galaxy morphology classification. Mach. Learn. Sci. Technol. 3 (3) (2022)
Mihailo Isakov, Mikaela Currier, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Glenn K. Lockwood, Michel A. Kinsy
A Taxonomy of Error Sources in HPC I/O Machine Learning Models. CoRR (2022)
Matthieu Dorier, Romain Egele, Prasanna Balaprakash, Jaehoon Koo, Sandeep Madireddy, Srinivasan Ramesh, Allen D. Malony, Robert B. Ross
HPC Storage Service Autotuning Using Variational-Autoencoder-Guided Asynchronous Bayesian Optimization. CoRR (2022)
Sumegha Premchandar, Sandeep Madireddy, Sanket Jantre, Prasanna Balaprakash
Unified Probabilistic Neural Architecture and Weight Ensembling Improves Model Robustness. CoRR (2022)
Aleksandra Ciprijanovic, Ashia Lewis, Kevin Pedro, Sandeep Madireddy, Brian Nord, Gabriel N. Perdue, Stefan M. Wild
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection. CoRR (2022)
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, Tomas E. Muller 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 Krupa, Pan Li, Sandeep Madireddy, Ethan Marx, Patrick McCormack, Andres Meza, Jovan Mitrevski, Mohammed Attia Mohammed, Farouk Mokhtar, Eric Moreno, Srishti Nagu, Rohin Narayan, Noah Palladino, Zhiqiang Que, Sang Eon Park, Subramanian Ramamoorthy, Dylan Rankin, Simon Rothman, Ashish Sharma, Sioni Summers, Pietro Vischia, Jean-Roch Vlimant, Olivia Weng
Applications and Techniques for Fast Machine Learning in Science. CoRR (2021)
Aleksandra Ciprijanovic, Diana Kafkes, K. Downey, S. Jenkins, Gabriel N. Perdue, Sandeep Madireddy, T. Johnston, Gregory F. Snyder, Brian Nord
DeepMerge II: Building Robust Deep Learning Algorithms for Merging Galaxy Identification Across Domains. CoRR (2021)
Aleksandra Ciprijanovic, Diana Kafkes, Gregory F. Snyder, F. Javier Sánchez, Gabriel Nathan Perdue, Kevin Pedro, Brian Nord, Sandeep Madireddy, Stefan M. Wild
DeepAdversaries: Examining the Robustness of Deep Learning Models for Galaxy Morphology Classification. CoRR (2021)
Aleksandra Ciprijanovic, Diana Kafkes, Gabriel N. Perdue, Kevin Pedro, Gregory F. Snyder, F. Javier Sánchez, Sandeep Madireddy, Stefan M. Wild, Brian Nord
Robustness of deep learning algorithms in astronomy - galaxy morphology studies. CoRR (2021)
Sandeep Madireddy, Ji Hwan Park, Sunwoo Lee, Prasanna Balaprakash, Shinjae Yoo, Wei-keng Liao, Cory D. Hauck, M. Paul Laiu, Richard Archibald
In situ compression artifact removal in scientific data using deep transfer learning and experience replay. Mach. Learn. Sci. Technol. 2 (2) (2021)
Mihailo Isakov, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Michel A. Kinsy
HPC I/O throughput bottleneck analysis with explainable local models. SC (2020)
Eliakin Del Rosario, Mikaela Currier, Mihailo Isakov, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Kevin Harms, Shane Snyder, Michel A. Kinsy
Gauge: An Interactive Data-Driven Visualization Tool for HPC Application I/O Performance Analysis. PDSW@SC (2020)
Aleksandra Ciprijanovic, Diana Kafkes, S. Jenkins, K. Downey, Gabriel N. Perdue, Sandeep Madireddy, T. Johnston, Brian Nord
Domain adaptation techniques for improved cross-domain study of galaxy mergers. CoRR (2020)
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
Multilayer Neuromodulated Architectures for Memory-Constrained Online Continual Learning. CoRR (2020)
Mihailo Isakov, Eliakin Del Rosario, Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert B. Ross, Michel A. Kinsy
Toward Generalizable Models of I/O Throughput. ROSS@SC (2020)
Romit Maulik, Vishwas Rao, Sandeep Madireddy, Bethany Lusch, Prasanna Balaprakash
Using recurrent neural networks for nonlinear component computation in advection-dominated reduced-order models. CoRR (2019)
Sunwoo Lee, Qiao Kang, Sandeep Madireddy, Prasanna Balaprakash, Ankit Agrawal, Alok N. Choudhary, Richard Archibald, Wei-keng Liao
Improving Scalability of Parallel CNN Training by Adjusting Mini-Batch Size at Run-Time. IEEE BigData (2019)
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning. ICONS (2019)
Sandeep Madireddy, Angel Yanguas-Gil, Prasanna Balaprakash
Neuromorphic Architecture Optimization for Task-Specific Dynamic Learning. CoRR (2019)
Sandeep Madireddy, Nan Li, Nesar Ramachandra, Prasanna Balaprakash, Salman Habib
Modular Deep Learning Analysis of Galaxy-Scale Strong Lensing Images. CoRR (2019)
Peihong Jiang, Hieu Doan, Sandeep Madireddy, Rajeev Surendran Assary, Prasanna Balaprakash
Value-Added Chemical Discovery Using Reinforcement Learning. CoRR (2019)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Glenn K. Lockwood, Robert B. Ross, Shane Snyder, Stefan M. Wild
Adaptive Learning for Concept Drift in Application Performance Modeling. ICPP (2019)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild
Machine Learning Based Parallel I/O Predictive Modeling: A Case Study on Lustre File Systems. ISC (2018)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild
Modeling I/O Performance Variability Using Conditional Variational Autoencoders. CLUSTER (2018)
Sandeep Madireddy, Prasanna Balaprakash, Philip H. Carns, Robert Latham, Robert B. Ross, Shane Snyder, Stefan M. Wild
Analysis and Correlation of Application I/O Performance and System-Wide I/O Activity. NAS (2017)