Prabhat

Orcid: 0000-0003-3281-5186

Affiliations:
  • Lawrence Berkeley National Laboratory, NERSC


According to our database1, Prabhat authored at least 86 papers between 2005 and 2021.

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Bibliography

2021
Learning from learning machines: a new generation of AI technology to meet the needs of science.
CoRR, 2021

2020
Characterizing Extreme Weather in a Changing Climate
PhD thesis, 2020

Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems.
J. Comput. Phys., 2020

Track Seeding and Labelling with Embedded-space Graph Neural Networks.
CoRR, 2020

MeshfreeFlowNet: a physics-constrained deep continuous space-time super-resolution framework.
Proceedings of the International Conference for High Performance Computing, 2020

Scaling of Union of Intersections for Inference of Granger Causal Networks from Observational Data.
Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

Atmospheric Blocking Pattern Recognition in Global Climate Model Simulation Data.
Proceedings of the 25th International Conference on Pattern Recognition, 2020

2019
Optimizing I/O Performance of HPC Applications with Autotuning.
ACM Trans. Parallel Comput., 2019

Deep learning and process understanding for data-driven Earth system science.
Nat., 2019

Cataloging the visible universe through Bayesian inference in Julia at petascale.
J. Parallel Distributed Comput., 2019

Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs.
CoRR, 2019

Towards Unsupervised Segmentation of Extreme Weather Events.
CoRR, 2019

Alchemist: An Apache Spark ⇔ MPI interface.
Concurr. Comput. Pract. Exp., 2019

Deep-Hurricane-Tracker: Tracking and Forecasting Extreme Climate Events.
Proceedings of the IEEE Winter Conference on Applications of Computer Vision, 2019

Acceleration of Scientific Deep Learning Models on Heterogeneous Computing Platform with Intel<sup>®</sup> FPGAs.
Proceedings of the High Performance Computing, 2019

Highly-Ccalable, Physics-Informed GANs for Learning Solutions of Stochastic PDEs.
Proceedings of the Third IEEE/ACM Workshop on Deep Learning on Supercomputers, 2019

DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems.
Proceedings of the 2019 IEEE/ACM Workshop on Machine Learning in High Performance Computing Environments, 2019

Etalumis: bringing probabilistic programming to scientific simulators at scale.
Proceedings of the International Conference for High Performance Computing, 2019

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Spherical CNNs on Unstructured Grids.
Proceedings of the 7th International Conference on Learning Representations, 2019

Learning to Focus and Track Extreme Climate Events.
Proceedings of the 30th British Machine Vision Conference 2019, 2019

2018
Optimizing the Union of Intersections LASSO (UoI<sub>LASSO</sub>) and Vector Autoregressive (UoI<sub>VAR</sub>) Algorithms for Improved Statistical Estimation at Scale.
CoRR, 2018

Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model.
CoRR, 2018

Approximate Inference for Constructing Astronomical Catalogs from Images.
CoRR, 2018

International Neuroscience Initiatives through the Lens of High-Performance Computing.
Computer, 2018

Interactive Distributed Deep Learning with Jupyter Notebooks.
Proceedings of the High Performance Computing, 2018

CosmoFlow: using deep learning to learn the universe at scale.
Proceedings of the International Conference for High Performance Computing, 2018

Exascale deep learning for climate analytics.
Proceedings of the International Conference for High Performance Computing, 2018

Evaluation of HPC Application I/O on Object Storage Systems.
Proceedings of the 3rd IEEE/ACM International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems, 2018

Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Cataloging the Visible Universe Through Bayesian Inference at Petascale.
Proceedings of the 2018 IEEE International Parallel and Distributed Processing Symposium, 2018

Graph Neural Networks for IceCube Signal Classification.
Proceedings of the 17th IEEE International Conference on Machine Learning and Applications, 2018

ArrayBridge: Interweaving Declarative Array Processing in SciDB with Imperative HDF5-Based Programs.
Proceedings of the 34th IEEE International Conference on Data Engineering, 2018

2017
Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer.
CoRR, 2017

Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators.
CoRR, 2017

Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC.
CoRR, 2017

An Assessment of Data Transfer Performance for Large-Scale Climate Data Analysis and Recommendations for the Data Infrastructure for CMIP6.
CoRR, 2017

ArrayBridge: Interweaving declarative array processing with high-performance computing.
CoRR, 2017

Deep learning at 15PF: supervised and semi-supervised classification for scientific data.
Proceedings of the International Conference for High Performance Computing, 2017

Galactos: computing the anisotropic 3-point correlation function for 2 billion galaxies.
Proceedings of the International Conference for High Performance Computing, 2017

Performance analysis of emerging data analytics and HPC workloads.
Proceedings of the 2nd Joint International Workshop on Parallel Data Storage & Data Intensive Scalable Computing Systems, 2017

ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Methods for Specifying Scientific Data Standards and Modeling Relationships with Applications to Neuroscience.
Frontiers Neuroinformatics, 2016

Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference.
CoRR, 2016

Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets.
CoRR, 2016

Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets.
CoRR, 2016

Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies.
CoRR, 2016

PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

A Multi-Platform Evaluation of the Randomized CX Low-Rank Matrix Factorization in Spark.
Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium Workshops, 2016

Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks.
Proceedings of the 15th IEEE International Conference on Machine Learning and Applications, 2016

Data Elevator: Low-Contention Data Movement in Hierarchical Storage System.
Proceedings of the 23rd IEEE International Conference on High Performance Computing, 2016

Matrix factorizations at scale: A comparison of scientific data analytics in spark and C+MPI using three case studies.
Proceedings of the 2016 IEEE International Conference on Big Data (IEEE BigData 2016), 2016

2015
Techniques for modeling large-scale HPC I/O workloads.
Proceedings of the 6th International Workshop on Performance Modeling, 2015

BD-CATS: big data clustering at trillion particle scale.
Proceedings of the International Conference for High Performance Computing, 2015

Pattern-driven parallel I/O tuning.
Proceedings of the 10th Parallel Data Storage Workshop, 2015

A Gaussian Process Model of Quasar Spectral Energy Distributions.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015

Scalable Bayesian Optimization Using Deep Neural Networks.
Proceedings of the 32nd International Conference on Machine Learning, 2015

Celeste: Variational inference for a generative model of astronomical images.
Proceedings of the 32nd International Conference on Machine Learning, 2015

A Multiplatform Study of I/O Behavior on Petascale Supercomputers.
Proceedings of the 24th International Symposium on High-Performance Parallel and Distributed Computing, 2015

Dynamic Model-Driven Parallel I/O Performance Tuning.
Proceedings of the 2015 IEEE International Conference on Cluster Computing, 2015

TECA: Petascale Pattern Recognition for Climate Science.
Proceedings of the Computer Analysis of Images and Patterns, 2015

2014
Improving parallel I/O autotuning with performance modeling.
Proceedings of the 23rd International Symposium on High-Performance Parallel and Distributed Computing, 2014

2013
A Parallel EM Algorithm for Model-Based Clustering Applied to the Exploration of Large Spatio-Temporal Data.
Technometrics, 2013

Parallelizing Gaussian Process Calculations in R
CoRR, 2013

Ultrascale Visualization of Climate Data.
Computer, 2013

Why high performance visual data analytics is both relevant and difficult.
Proceedings of the Visualization and Data Analysis 2013, 2013

Taming parallel I/O complexity with auto-tuning.
Proceedings of the International Conference for High Performance Computing, 2013

A framework for auto-tuning HDF5 applications.
Proceedings of the 22nd International Symposium on High-Performance Parallel and Distributed Computing, 2013

2012
TECA: A Parallel Toolkit for Extreme Climate Analysis.
Proceedings of the International Conference on Computational Science, 2012

Accelerating analysis of void space in porous materials on multicore and GPU platforms.
Int. J. High Perform. Comput. Appl., 2012

A System for Query Based Analysis and Visualization.
Proceedings of the 3rd International EuroVis Workshop on Visual Analytics, 2012

Parallel I/O, analysis, and visualization of a trillion particle simulation.
Proceedings of the SC Conference on High Performance Computing Networking, 2012

Abstract: Auto-Tuning of Parallel IO Parameters for HDF5 Applications.
Proceedings of the 2012 SC Companion: High Performance Computing, 2012

Experiences with 100Gbps network applications.
Proceedings of the DIDC'12, 2012

2011
FastQuery: A General Indexing and Querying System for Scientific Data.
Proceedings of the Scientific and Statistical Database Management, 2011

Parallel index and query for large scale data analysis.
Proceedings of the Conference on High Performance Computing Networking, 2011

Parallel Kriging Analysis for Large Spatial Datasets.
Proceedings of the Data Mining Workshops (ICDMW), 2011

FastQuery: A Parallel Indexing System for Scientific Data.
Proceedings of the 2011 IEEE International Conference on Cluster Computing (CLUSTER), 2011

2010
Coupling visualization and data analysis for knowledge discovery from multi-dimensional scientific data.
Proceedings of the International Conference on Computational Science, 2010

Extreme Scaling of Production Visualization Software on Diverse Architectures.
IEEE Computer Graphics and Applications, 2010

2008
A Comparative Study of Desktop, Fishtank, and Cave Systems for the Exploration of Volume Rendered Confocal Data Sets.
IEEE Trans. Vis. Comput. Graph., 2008

High performance multivariate visual data exploration for extremely large data.
Proceedings of the ACM/IEEE Conference on High Performance Computing, 2008

Automated Analysis for Detecting Beams in Laser Wakefield Simulations.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

2006
Adviser: Immersive Field Work for Planetary Geoscientists.
IEEE Computer Graphics and Applications, 2006

2005
Experiences in driving a cave with IBM scalable graphics engine-3 (SGE-3) prototypes.
Proceedings of the ACM Symposium on Virtual Reality Software and Technology, 2005


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