Prabhat - RankMe

101 papers A* 5A 19B 3C 6Misc 4Journal 44Unranked 19

Year	Rank	Type	Title / Venue / Authors
2024	C	`conf`	Impact of Discretization Techniques on Model Predictive Control of SRMs. IECON Prabhat, A. V. Ravi Teja
2021	J	`jnl`	Learning from learning machines: a new generation of AI technology to meet the needs of science. CoRR Luca Pion-Tonachini, Kristofer E. Bouchard, Héctor García Martín, Sean Peisert, W. Bradley Holtz, Anil Aswani, Dipankar Dwivedi, Haruko M. Wainwright, Ghanshyam Pilania, Benjamin Nachman, Babetta L. Marrone, Nicola Falco, Prabhat, Daniel B. Arnold, Alejandro Wolf-Yadlin, Sarah Powers, Sharlee Climer, Quinn Jackson, Ty Carlson, Michael Sohn, Petrus H. Zwart, Neeraj Kumar, Amy Justice, Claire J. Tomlin, Daniel A. Jacobson, Gos Micklem, Georgios V. Gkoutos, Peter J. Bickel, Jean-Baptiste Cazier, Juliane Müller, Bobbie-Jo Webb-Robertson, Rick Stevens, Mark Anderson, Kenneth Kreutz-Delgado, Michael W. Mahoney, James B. Brown
2020	B	`conf`	Atmospheric Blocking Pattern Recognition in Global Climate Model Simulation Data. ICPR Grzegorz Muszynski, Prabhat, Jan Balewski, Karthik Kashinath, Michael F. Wehner, Vitaliy Kurlin
2020	—	`—`	Characterizing Extreme Weather in a Changing Climate Prabhat
2020	J	`jnl`	Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems. J. Comput. Phys. Jinlong Wu, Karthik Kashinath, Adrian Albert, Dragos Chirila, Prabhat, Heng Xiao
2020	J	`jnl`	MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework. CoRR Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar
2020	A	`conf`	MeshfreeFlowNet: a physics-constrained deep continuous space-time super-resolution framework. SC Chiyu Max Jiang, Soheil Esmaeilzadeh, Kamyar Azizzadenesheli, Karthik Kashinath, Mustafa Mustafa, Hamdi A. Tchelepi, Philip Marcus, Prabhat, Anima Anandkumar
2020	A	`conf`	Scaling of Union of Intersections for Inference of Granger Causal Networks from Observational Data. IPDPS Mahesh Balasubramanian, Trevor D. Ruiz, Brandon Cook, Prabhat, Sharmodeep Bhattacharyya, Aviral Shrivastava, Kristofer E. Bouchard
2020	J	`jnl`	Track Seeding and Labelling with Embedded-space Graph Neural Networks. CoRR Nicholas Choma, Daniel Murnane, Xiangyang Ju, Paolo Calafiura, Sean Conlon, Steven Farrell, Prabhat, Giuseppe Cerati, Lindsey Gray, Thomas Klijnsma, Jim Kowalkowski, Panagiotis Spentzouris, Jean-Roch Vlimant, Maria Spiropulu, Adam Aurisano, Jeremy Hewes, Aristeidis Tsaris, Kazuhiro Terao, Tracy L. Usher
2019	—	`conf`	Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel ISC Workshops Chao Jiang, Dave Ojika, Thorsten Kurth, Prabhat, Sofia Vallecorsa, Bhavesh Patel, Herman Lam
2019	J	`jnl`	Alchemist: An Apache Spark ⇔ MPI interface. Concurr. Comput. Pract. Exp. Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Jey Kottalam, Lisa Gerhardt, Prabhat, Michael F. Ringenburg, Kristyn J. Maschhoff
2019	J	`jnl`	Cataloging the visible universe through Bayesian inference in Julia at petascale. J. Parallel Distributed Comput. Jeffrey Regier, Keno Fischer, Kiran Pamnany, Andreas Noack, Jarrett Revels, Maximilian Lam, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat
2019	J	`jnl`	Deep learning and process understanding for data-driven Earth system science. Nat. Markus Reichstein, Gustau Camps-Valls, Bjorn Stevens, Martin Jung, Joachim Denzler, Nuno Carvalhais, Prabhat
2019	A	`conf`	Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events. WACV Sookyung Kim, Hyojin Kim, Joonseok Lee, Sangwoong Yoon, Samira Ebrahimi Kahou, Karthik Kashinath, Prabhat
2019	—	`conf`	DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems. MLHPC@SC Adam Rupe, Prabhat, James P. Crutchfield, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor W. Lee
2019	J	`jnl`	DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems. CoRR Adam Rupe, Nalini Kumar, Vladislav Epifanov, Karthik Kashinath, Oleksandr Pavlyk, Frank Schlimbach, Mostofa Patwary, Sergey Maidanov, Victor W. Lee, Prabhat, James P. Crutchfield
2019	A*	`conf`	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. NeurIPS Atilim Gunes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Saeid Naderiparizi, Andreas Munk, Jialin Liu, Bradley Gram-Hansen, Gilles Louppe, Lawrence Meadows, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	J	`jnl`	Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale. CoRR Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	A	`conf`	Etalumis: bringing probabilistic programming to scientific simulators at scale. SC Atilim Günes Baydin, Lei Shao, Wahid Bhimji, Lukas Heinrich, Lawrence Meadows, Jialin Liu, Andreas Munk, Saeid Naderiparizi, Bradley Gram-Hansen, Gilles Louppe, Mingfei Ma, Xiaohui Zhao, Philip H. S. Torr, Victor W. Lee, Kyle Cranmer, Prabhat, Frank Wood
2019	—	`conf`	Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs. DLS@SC Liu Yang, Prabhat, George E. Karniadakis, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston
2019	J	`jnl`	Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs. CoRR Liu Yang, Sean Treichler, Thorsten Kurth, Keno Fischer, David A. Barajas-Solano, Joshua Romero, Valentin Churavy, Alexandre M. Tartakovsky, Michael Houston, Prabhat, George E. Karniadakis
2019	A	`conf`	Learning to Focus and Track Extreme Climate Events. BMVC Sookyung Kim, Sunghyun Park, Sunghyo Chung, Joonseok Lee, Yunsung Lee, Hyojin Kim, Prabhat, Jaegul Choo
2019	J	`jnl`	Optimizing I/O Performance of HPC Applications with Autotuning. ACM Trans. Parallel Comput. Babak Behzad, Surendra Byna, Prabhat, Marc Snir
2019	—	`conf`	Spherical CNNs on Unstructured Grids. ICLR (Poster) Chiyu Max Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Nießner
2019	J	`jnl`	Spherical CNNs on Unstructured Grids. CoRR Chiyu Max Jiang, Jingwei Huang, Karthik Kashinath, Prabhat, Philip Marcus, Matthias Nießner
2019	J	`jnl`	Towards Unsupervised Segmentation of Extreme Weather Events. CoRR Adam Rupe, Karthik Kashinath, Nalini Kumar, Victor W. Lee, Prabhat, James P. Crutchfield
2018	A*	`conf`	Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. KDD Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Lisa Gerhardt, Prabhat, Jey Kottalam, Michael F. Ringenburg, Kristyn J. Maschhoff
2018	J	`jnl`	Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist. CoRR Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Lisa Gerhardt, Prabhat, Jey Kottalam, Michael F. Ringenburg, Kristyn J. Maschhoff
2018	J	`jnl`	Alchemist: An Apache Spark MPI Interface. CoRR Alex Gittens, Kai Rothauge, Shusen Wang, Michael W. Mahoney, Jey Kottalam, Lisa Gerhardt, Prabhat, Michael F. Ringenburg, Kristyn J. Maschhoff
2018	J	`jnl`	Approximate Inference for Constructing Astronomical Catalogs from Images. CoRR Jeffrey Regier, Andrew C. Miller, David Schlegel, Ryan P. Adams, Jon D. McAuliffe, Prabhat
2018	A*	`conf`	ArrayBridge: Interweaving Declarative Array Processing in SciDB with Imperative HDF5-Based Programs. ICDE Haoyuan Xing, Sofoklis Floratos, Spyros Blanas, Suren Byna, Prabhat, Kesheng Wu, Paul Brown
2018	A	`conf`	Cataloging the Visible Universe Through Bayesian Inference at Petascale. IPDPS Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat
2018	J	`jnl`	Cataloging the Visible Universe through Bayesian Inference at Petascale. CoRR Jeffrey Regier, Kiran Pamnany, Keno Fischer, Andreas Noack, Maximilian Lam, Jarrett Revels, Steve Howard, Ryan Giordano, David Schlegel, Jon McAuliffe, Rollin C. Thomas, Prabhat
2018	J	`jnl`	CosmoFlow: Using Deep Learning to Learn the Universe at Scale. CoRR Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Karna, Diana Moise, Simon J. Pennycook, Kristyn J. Maschhoff, Jason Sewall, Nalini Kumar, Shirley Ho, Michael F. Ringenburg, Prabhat, Victor W. Lee
2018	A	`conf`	CosmoFlow: using deep learning to learn the universe at scale. SC Amrita Mathuriya, Deborah Bard, Peter Mendygral, Lawrence Meadows, James Arnemann, Lei Shao, Siyu He, Tuomas Kärnä, Diana Moise, Simon J. Pennycook, Kristyn J. Maschhoff, Jason Sewall, Nalini Kumar, Shirley Ho, Michael F. Ringenburg, Prabhat, Victor W. Lee
2018	J	`jnl`	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model. CoRR Atilim Gunes Baydin, Lukas Heinrich, Wahid Bhimji, Bradley Gram-Hansen, Gilles Louppe, Lei Shao, Prabhat, Kyle Cranmer, Frank D. Wood
2018	—	`conf`	Evaluation of HPC Application I/O on Object Storage Systems. PDSW-DISCS@SC Jialin Liu, Quincey Koziol, Gregory F. Butler, Neil Fortner, Mohamad Chaarawi, Houjun Tang, Suren Byna, Glenn K. Lockwood, Ravi Cheema, Kristy A. Kallback-Rose, Damian Hazen, Prabhat
2018	J	`jnl`	Exascale Deep Learning for Climate Analytics. CoRR Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
2018	A	`conf`	Exascale deep learning for climate analytics. SC Thorsten Kurth, Sean Treichler, Joshua Romero, Mayur Mudigonda, Nathan Luehr, Everett H. Phillips, Ankur Mahesh, Michael A. Matheson, Jack Deslippe, Massimiliano Fatica, Prabhat, Michael Houston
2018	C	`conf`	Graph Neural Networks for IceCube Signal Classification. ICMLA Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna
2018	J	`jnl`	Graph Neural Networks for IceCube Signal Classification. CoRR Nicholas Choma, Federico Monti, Lisa Gerhardt, Tomasz Palczewski, Zahra Ronaghi, Prabhat, Wahid Bhimji, Michael M. Bronstein, Spencer R. Klein, Joan Bruna
2018	—	`conf`	Interactive Distributed Deep Learning with Jupyter Notebooks. ISC Workshops Steven Andrew Farrell, Aaron Vose, Oliver Evans, Matthew L. Henderson, Shreyas Cholia, Fernando Pérez, Wahid Bhimji, Shane Canon, Rollin C. Thomas, Prabhat
2018	J	`jnl`	International Neuroscience Initiatives through the Lens of High-Performance Computing. Computer Kristofer E. Bouchard, James B. Aimone, Miyoung Chun, Thomas Dean, Michael Denker, Markus Diesmann, David Donofrio, Loren M. Frank, Narayanan Kasthuri, Christof Koch, Oliver Rübel, Horst D. Simon, Friedrich T. Sommer, Prabhat
2018	J	`jnl`	Optimizing the Union of Intersections LASSO (UoI CoRR Mahesh Balasubramanian, Trevor D. Ruiz, Brandon Cook, Sharmodeep Bhattacharyya, Prabhat, Aviral Shrivastava, Kristofer E. Bouchard
2017	J	`jnl`	An Assessment of Data Transfer Performance for Large-Scale Climate Data Analysis and Recommendations for the Data Infrastructure for CMIP6. CoRR Eli Dart, Michael F. Wehner, Prabhat
2017	J	`jnl`	ArrayBridge: Interweaving declarative array processing with high-performance computing. CoRR Haoyuan Xing, Sofoklis Floratos, Spyros Blanas, Suren Byna, Prabhat, Kesheng Wu, Paul Brown
2017	J	`jnl`	Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data. CoRR Thorsten Kurth, Jian Zhang, Nadathur Satish, Ioannis Mitliagkas, Evan Racah, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey
2017	J	`jnl`	Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC. CoRR Wahid Bhimji, Steven Andrew Farrell, Thorsten Kurth, Michela Paganini, Prabhat, Evan Racah
2017	A	`conf`	Deep learning at 15PF: supervised and semi-supervised classification for scientific data. SC Thorsten Kurth, Jian Zhang, Nadathur Satish, Evan Racah, Ioannis Mitliagkas, Md. Mostofa Ali Patwary, Tareq M. Malas, Narayanan Sundaram, Wahid Bhimji, Mikhail Smorkalov, Jack Deslippe, Mikhail Shiryaev, Srinivas Sridharan, Prabhat, Pradeep Dubey
2017	—	`conf`	ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events. NIPS Evan Racah, Christopher Beckham, Tegan Maharaj, Samira Ebrahimi Kahou, Prabhat, Chris Pal
2017	J	`jnl`	Galactos: Computing the Anisotropic 3-Point Correlation Function for 2 Billion Galaxies. CoRR Brian Friesen, Md. Mostofa Ali Patwary, Brian Austin, Nadathur Satish, Zachary Slepian, Narayanan Sundaram, Deborah Bard, Daniel J. Eisenstein, Jack Deslippe, Pradeep Dubey, Prabhat
2017	A	`conf`	Galactos: computing the anisotropic 3-point correlation function for 2 billion galaxies. SC Brian Friesen, Md. Mostofa Ali Patwary, Brian Austin, Nadathur Satish, Zachary Slepian, Narayanan Sundaram, Deborah Bard, Daniel J. Eisenstein, Jack Deslippe, Pradeep Dubey, Prabhat
2017	J	`jnl`	Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators. CoRR Mario Lezcano Casado, Atilim Gunes Baydin, David Martínez-Rubio, Tuan Anh Le, Frank D. Wood, Lukas Heinrich, Gilles Louppe, Kyle Cranmer, Karen Ng, Wahid Bhimji, Prabhat
2017	—	`conf`	Performance analysis of emerging data analytics and HPC workloads. PDSW-DISCS@SC Christopher S. Daley, Prabhat, Sudip S. Dosanjh, Nicholas J. Wright
2017	J	`jnl`	Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer. CoRR Amrita Mathuriya, Thorsten Kurth, Vivek Rane, Mustafa Mustafa, Lei Shao, Debbie Bard, Prabhat, Victor W. Lee
2017	—	`conf`	Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction. NIPS Kristofer E. Bouchard, Alejandro F. Bujan, Farbod Roosta-Khorasani, Shashanka Ubaru, Prabhat, Antoine Snijders, Jian-Hua Mao, Edward F. Chang, Michael W. Mahoney, Sharmodeep Bhattacharyya
2016	—	`conf`	A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark. IPDPS Workshops Alex Gittens, Jey Kottalam, Jiyan Yang, Michael F. Ringenburg, Jatin Chhugani, Evan Racah, Mohitdeep Singh, Yushu Yao, Curt Fischer, Oliver Rübel, Benjamin P. Bowen, Norman G. Lewis, Michael W. Mahoney, Venkat Krishnamurthy, Prabhat
2016	J	`jnl`	Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets. CoRR Yunjie Liu, Evan Racah, Prabhat, Joaquin Correa, Amir Khosrowshahi, David Lavers, Kenneth Kunkel, Michael F. Wehner, William D. Collins
2016	Misc	`conf`	Data Elevator: Low-Contention Data Movement in Hierarchical Storage System. HiPC Bin Dong, Suren Byna, Kesheng Wu, Prabhat, Hans Johansen, Jeffrey N. Johnson, Noel Keen
2016	J	`jnl`	Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference. CoRR Jeffrey Regier, Kiran Pamnany, Ryan Giordano, Rollin C. Thomas, David Schlegel, Jon McAuliffe, Prabhat
2016	J	`jnl`	Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies. CoRR Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat
2016	—	`conf`	Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies. IEEE BigData Alex Gittens, Aditya Devarakonda, Evan Racah, Michael F. Ringenburg, Lisa Gerhardt, Jey Kottalam, Jialin Liu, Kristyn J. Maschhoff, Shane Canon, Jatin Chhugani, Pramod Sharma, Jiyan Yang, James Demmel, Jim Harrell, Venkat Krishnamurthy, Michael W. Mahoney, Prabhat
2016	J	`jnl`	Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience. Frontiers Neuroinformatics Oliver Rübel, Max Dougherty, Prabhat, Peter Denes, David Conant, Edward F. Chang, Kristofer E. Bouchard
2016	A	`conf`	PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures. IPDPS Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
2016	J	`jnl`	PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures. CoRR Md. Mostofa Ali Patwary, Nadathur Rajagopalan Satish, Narayanan Sundaram, Jialin Liu, Peter J. Sadowski, Evan Racah, Surendra Byna, Craig Tull, Wahid Bhimji, Prabhat, Pradeep Dubey
2016	C	`conf`	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks. ICMLA Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
2016	J	`jnl`	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment using Deep Neural Networks. CoRR Evan Racah, Seyoon Ko, Peter J. Sadowski, Wahid Bhimji, Craig Tull, Sang-Yun Oh, Pierre Baldi, Prabhat
2016	J	`jnl`	Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets. CoRR Evan Racah, Christopher Beckham, Tegan Maharaj, Prabhat, Christopher J. Pal
2015	—	`conf`	A Gaussian Process Model of Quasar Spectral Energy Distributions. NIPS Andrew C. Miller, Albert Wu, Jeffrey Regier, Jon McAuliffe, Dustin Lang, Prabhat, David Schlegel, Ryan P. Adams
2015	A	`conf`	A Multiplatform Study of I/O Behavior on Petascale Supercomputers. HPDC Huong Luu, Marianne Winslett, William Gropp, Robert B. Ross, Philip H. Carns, Kevin Harms, Prabhat, Surendra Byna, Yushu Yao
2015	A	`conf`	BD-CATS: big data clustering at trillion particle scale. SC Md. Mostofa Ali Patwary, Surendra Byna, Nadathur Rajagopalan Satish, Narayanan Sundaram, Zarija Lukic, Vadim Roytershteyn, Michael J. Anderson, Yushu Yao, Prabhat, Pradeep Dubey
2015	A*	`conf`	Celeste: Variational inference for a generative model of astronomical images. ICML Jeffrey Regier, Andrew C. Miller, Jon McAuliffe, Ryan P. Adams, Matthew D. Hoffman, Dustin Lang, David Schlegel, Prabhat
2015	C	`conf`	Dynamic Model-Driven Parallel I/O Performance Tuning. CLUSTER Babak Behzad, Surendra Byna, Stefan M. Wild, Prabhat, Marc Snir
2015	—	`conf`	Pattern-driven parallel I/O tuning. PDSW@SC Babak Behzad, Surendra Byna, Prabhat, Marc Snir
2015	A*	`conf`	Scalable Bayesian Optimization Using Deep Neural Networks. ICML Jasper Snoek, Oren Rippel, Kevin Swersky, Ryan Kiros, Nadathur Satish, Narayanan Sundaram, Md. Mostofa Ali Patwary, Prabhat, Ryan P. Adams
2015	—	`conf`	TECA: Petascale Pattern Recognition for Climate Science. CAIP (2) Prabhat, Surendra Byna, Venkatram Vishwanath, Eli Dart, Michael F. Wehner, William D. Collins
2015	—	`conf`	Techniques for modeling large-scale HPC I/O workloads. PMBS@SC Shane Snyder, Philip H. Carns, Robert Latham, Misbah Mubarak, Robert B. Ross, Christopher D. Carothers, Babak Behzad, Huong Vu Thanh Luu, Surendra Byna, Prabhat
2014	A	`conf`	Improving parallel I/O autotuning with performance modeling. HPDC Babak Behzad, Surendra Byna, Stefan M. Wild, Prabhat, Marc Snir
2013	J	`jnl`	A Parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data. Technometrics Wei-Chen Chen, George Ostrouchov, David Pugmire, Prabhat, Michael F. Wehner
2013	A	`conf`	A framework for auto-tuning HDF5 applications. HPDC Babak Behzad, Joey Huchette, Huong Vu Thanh Luu, Ruth A. Aydt, Surendra Byna, Yushu Yao, Quincey Koziol, Prabhat
2013	J	`jnl`	Parallelizing Gaussian Process Calculations in R CoRR Christopher J. Paciorek, Benjamin Lipshitz, Wei Zhuo, Prabhat, Cari Kaufman, Rollin C. Thomas
2013	A	`conf`	Taming parallel I/O complexity with auto-tuning. SC Babak Behzad, Huong Vu Thanh Luu, Joseph Huchette, Surendra Byna, Prabhat, Ruth A. Aydt, Quincey Koziol, Marc Snir
2013	J	`jnl`	Ultrascale Visualization of Climate Data. Computer Dean N. Williams, Peer-Timo Bremer, Charles M. Doutriaux, John Patchett, Sean Williams, Galen M. Shipman, Ross Miller, David Pugmire, Brian E. Smith, Chad A. Steed, E. Wes Bethel, Hank Childs, Harinarayan Krishnan, Prabhat, Michael F. Wehner, Cláudio T. Silva, Emanuele Santos, David Koop, Tommy Ellqvist, Jorge Poco, Berk Geveci, Aashish Chaudhary, Andy Bauer, Alexander Pletzer, Dave Kindig, Gerald Potter, Thomas P. Maxwell
2013	Misc	`conf`	Why high performance visual data analytics is both relevant and difficult. Visualization and Data Analysis E. Wes Bethel, Prabhat, Surendra Byna, Oliver Rübel, K. John Wu, Michael F. Wehner
2012	—	`conf`	A System for Query Based Analysis and Visualization. EuroVA@EuroVis Allen R. Sanderson, Brad Whitlock, Oliver Rübel, Hank Childs, Gunther H. Weber, Prabhat, Kenseng Wu
2012	—	`conf`	Abstract: Auto-Tuning of Parallel IO Parameters for HDF5 Applications. SC Companion Babak Behzad, Joey Huchette, Huong Luu, Ruth A. Aydt, Quincey Koziol, Prabhat, Surendra Byna, Mohamad Chaarawi, Yushu Yao
2012	J	`jnl`	Accelerating analysis of void space in porous materials on multicore and GPU platforms. Int. J. High Perform. Comput. Appl. Richard L. Martin, Prabhat, David Donofrio, James A. Sethian, Maciej Haranczyk
2012	—	`conf`	Experiences with 100Gbps network applications. DICT@HPDC Mehmet Balman, Eric Pouyoul, Yushu Yao, E. Wes Bethel, Burlen Loring, Prabhat, John Shalf, Alex Sim, Brian L. Tierney
2012	A	`conf`	Parallel I/O, analysis, and visualization of a trillion particle simulation. SC Surendra Byna, Jerry Chi-Yuan Chou, Oliver Rübel, Prabhat, Homa Karimabadi, William S. Daughton, Vadim Roytershteyn, E. Wes Bethel, Mark Howison, Ke-Jou Hsu, Kuan-Wu Lin, Arie Shoshani, Andrew Uselton, Kesheng Wu
2012	Misc	`conf`	TECA: A Parallel Toolkit for Extreme Climate Analysis. ICCS Prabhat, Oliver Rübel, Surendra Byna, Kesheng Wu, Fuyu Li, Michael F. Wehner, Wes Bethel
2011	B	`conf`	FastQuery: A General Indexing and Querying System for Scientific Data. SSDBM Jerry Chi-Yuan Chou, Kesheng Wu, Prabhat
2011	C	`conf`	FastQuery: A Parallel Indexing System for Scientific Data. CLUSTER Jerry Chi-Yuan Chou, Kesheng Wu, Prabhat
2011	—	`conf`	Parallel Kriging Analysis for Large Spatial Datasets. ICDM Workshops Wei Zhuo, Prabhat, Christopher J. Paciorek, Cari Kaufman, Wes Bethel
2011	A	`conf`	Parallel index and query for large scale data analysis. SC Jerry Chi-Yuan Chou, Mark Howison, Brian Austin, Kesheng Wu, Ji Qiang, E. Wes Bethel, Arie Shoshani, Oliver Rübel, Prabhat, Robert D. Ryne
2010	Misc	`conf`	Coupling visualization and data analysis for knowledge discovery from multi-dimensional scientific data. ICCS Oliver Rübel, Sean Ahern, E. Wes Bethel, Mark D. Biggin, Hank Childs, Estelle Cormier-Michel, Angela H. DePace, Michael B. Eisen, Charless C. Fowlkes, Cameron G. R. Geddes, Hans Hagen, Bernd Hamann, Min-Yu Huang, Soile V. E. Keränen, David W. Knowles, Cris L. Luengo Hendriks, Jitendra Malik, Jeremy S. Meredith, Peter Messmer, Prabhat
2010	J	`jnl`	Extreme Scaling of Production Visualization Software on Diverse Architectures. IEEE Computer Graphics and Applications Hank Childs, David Pugmire, Sean Ahern, Brad Whitlock, Mark Howison, Prabhat, Gunther H. Weber, E. Wes Bethel
2008	J	`jnl`	A Comparative Study of Desktop, Fishtank, and Cave Systems for the Exploration of Volume Rendered Confocal Data Sets. IEEE Trans. Vis. Comput. Graph. Prabhat, Andrew S. Forsberg, Michael Katzourin, Kristi Wharton, Mel Slater
2008	C	`conf`	Automated Analysis for Detecting Beams in Laser Wakefield Simulations. ICMLA Daniela Mayumi Ushizima, Oliver Rübel, Prabhat, Gunther H. Weber, E. Wes Bethel, Cecilia R. Aragon, Cameron G. R. Geddes, Estelle Cormier-Michel, Bernd Hamann, Peter Messmer, Hans Hagen
2008	A	`conf`	High performance multivariate visual data exploration for extremely large data. SC Oliver Rübel, Prabhat, Kesheng Wu, Hank Childs, Jeremy S. Meredith, Cameron G. R. Geddes, Estelle Cormier-Michel, Sean Ahern, Gunther H. Weber, Peter Messmer, Hans Hagen, Bernd Hamann, E. Wes Bethel
2006	J	`jnl`	Adviser: Immersive Field Work for Planetary Geoscientists. IEEE Computer Graphics and Applications Andrew S. Forsberg, Prabhat, Graff Haley, Andrew Bragdon, Joseph Levy, Caleb I. Fassett, David Shean, James W. Head III, Sarah Milkovich, Mark A. Duchaineau
2005	B	`conf`	Experiences in driving a cave with IBM scalable graphics engine-3 (SGE-3) prototypes. VRST Prabhat, Samuel G. Fulcomer