Michael A. Matheson

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All published works

Action	Title	Year	Authors
+ PDF Chat	PLANC	2021	Srinivas Eswar Koby Hayashi Grey Ballard Ramakrishnan Kannan Michael A. Matheson Haesun Park
+	Towards the Development of Entropy-Based Anomaly Detection in an Astrophysics Simulation	2020	Drew Schmidt O. E. Bronson Messer M. Todd Young Michael A. Matheson
+	PLANC: Parallel Low Rank Approximation with Non-negativity Constraints	2019	Srinivas Eswar Koby Hayashi Grey Ballard Ramakrishnan Kannan Michael A. Matheson Haesun Park
+	Exascale Deep Learning for Scientific Inverse Problems	2019	Nouamane Laanait Joshua Romero Junqi Yin M. Todd Young Sean Treichler Vitalii Starchenko Albina Y. Borisevich A. E. Sergeev Michael A. Matheson
+	Exascale deep learning for climate analytics	2018	Thorsten Kurth Sean Treichler Joshua Romero Mayur Mudigonda Nathan Luehr Everett Phillips Ankur Mahesh Michael A. Matheson Jack Deslippe Massimiliano Fatica
+	Defining Big Data Analytics Benchmarks for Next Generation Supercomputers.	2018	Drew Schmidt Junqi Yin Michael A. Matheson O. E. Bronson Messer Mallikarjun Shankar
+ PDF Chat	Exascale Deep Learning for Climate Analytics	2018	Thorsten Kurth Sean Treichler Joshua Romero Mayur Mudigonda Nathan Luehr Everett Phillips A Mahesh Michael A. Matheson Jack Deslippe Massimiliano Fatica

Common Coauthors

Coauthor	Papers Together
Joshua Romero	3
Sean Treichler	3
Massimiliano Fatica	2
Michael Houston	2
Haesun Park	2
Ramakrishnan Kannan	2
Koby Hayashi	2
O. E. Bronson Messer	2
Prabhat Prabhat	2
M. Todd Young	2
Jack Deslippe	2
Thorsten Kurth	2
Junqi Yin	2
Drew Schmidt	2
Mayur Mudigonda	2
Everett Phillips	2
Nathan Luehr	2
Grey Ballard	2
Srinivas Eswar	2
A. E. Sergeev	1
A Mahesh	1
Mallikarjun Shankar	1
Vitalii Starchenko	1
Albina Y. Borisevich	1
Ankur Mahesh	1
Nouamane Laanait	1

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	Horovod: fast and easy distributed deep learning in TensorFlow	2018	Alexander Sergeev Mike Del Balso	3
+ PDF Chat	The One Hundred Layers Tiramisu: Fully Convolutional DenseNets for Semantic Segmentation	2017	Simon Jégou Michal Drozdzal David Vázquez Adriana Romero Yoshua Bengio	3
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	3
+	A Flexible and Efficient Algorithmic Framework for Constrained Matrix and Tensor Factorization	2016	Kejun Huang Nicholas D. Sidiropoulos Athanasios P. Liavas	2
+	Alternating projected Barzilai-Borwein methods for nonnegative matrix factorization.	2009	Liangxiu Han Michael Neumann Upendra Prasad	2
+	Scikit-learn: Machine Learning in Python	2012	Fabián Pedregosa Gaël Varoquaux Alexandre Gramfort Vincent Michel Bertrand Thirion Olivier Grisel Mathieu Blondel Peter Prettenhofer Ron J. Weiss Vincent Dubourg	2
+ PDF Chat	Exploiting Efficient Representations in Large-Scale Tensor Decompositions	2019	Nico Vervliet Otto Debals Lieven De Lathauwer	2
+	Extremely Large Minibatch SGD: Training ResNet-50 on ImageNet in 15 Minutes	2017	Takuya Akiba Shuji Suzuki Keisuke Fukuda	2
+	Highly Scalable Deep Learning Training System with Mixed-Precision: Training ImageNet in Four Minutes	2018	Xianyan Jia Shutao Song Wei He Yangzihao Wang Haidong Rong Feihu Zhou Liqiang Xie Zhenyu Guo Yuanzhou Yang Li-Wei Yu	2
+ PDF Chat	Accelerating alternating least squares for tensor decomposition by pairwise perturbation	2022	Linjian Ma Edgar Solomonik	2
+ PDF Chat	Exascale Deep Learning for Climate Analytics	2018	Thorsten Kurth Sean Treichler Joshua Romero Mayur Mudigonda Nathan Luehr Everett Phillips A Mahesh Michael A. Matheson Jack Deslippe Massimiliano Fatica	2
+	Parallel Nonnegative CP Decomposition of Dense Tensors	2018	Grey Ballard Koby Hayashi Kannan Ramakrishnan	2
+	Automatic Chemical Design Using a Data-Driven Continuous Representation of Molecules	2018	Rafael Gómez‐Bombarelli Jennifer N. Wei David Duvenaud José Miguel Hernández-Lobato Benjamín Sánchez-Lengeling Dennis Sheberla Jorge Aguilera‐Iparraguirre Timothy Hirzel Ryan P. Adams Alán Aspuru‐Guzik	2
+	Fast and guaranteed tensor decomposition via sketching	2015	Yining Wang Hsiao-Yu Fish Tung Alex Smola Anima Anandkumar	2
+	GlobeNet: Convolutional Neural Networks for Typhoon Eye Tracking from Remote Sensing Imagery	2017	Seungkyun Hong Seongchan Kim Minsu Joh Sa-Kwang Song	2
+	Numerical tensor calculus	2014	Wolfgang Hackbusch	2
+	Randomized nonnegative matrix factorization	2018	N. Benjamin Erichson Ariana Mendible Sophie Wihlborn J. Nathan Kutz	2
+	Nesterov-Based Alternating Optimization for Nonnegative Tensor Factorization: Algorithm and Parallel Implementation	2017	Athanasios P. Liavas Georgios Kostoulas Georgios Lourakis Kejun Huang Nicholas D. Sidiropoulos	2
+	A weighted non-negative least squares algorithm for three-way ‘PARAFAC’ factor analysis	1997	Pentti Paatero	2
+ PDF Chat	Parallel Candecomp/Parafac Decomposition of Sparse Tensors Using Dimension Trees	2018	Oguz Kaya Bora Uçar	2
+	Tensor Decompositions and Applications	2009	Tamara G. Kolda Brett W. Bader	2
+ PDF Chat	CosmoFlow: Using Deep Learning to Learn the Universe at Scale	2018	Amrita Mathuriya Deborah Bard P. J. Mendygral Lawrence Meadows James Arnemann Lei Shao Siyu He Tuomas Kärnä Diana Moise S. J. Pennycook	2
+	Block-randomized Stochastic Proximal Gradient for Constrained Low-rank Tensor Factorization	2019	Xiao Fu Cheng Gao Hoi-To Wai Kejun Huang	2
+	CosmoFlow: Using Deep Learning to Learn the Universe at Scale	2018	Amrita Mathuriya Deborah Bard P. J. Mendygral Lawrence Meadows James Arnemann Lei Shao Siyu He Tuomas Kärnä Daina Moise S. J. Pennycook	2
+	Nonnegative Matrix and Tensor Factorization [Lecture Notes]	2008	Andrzej Cichocki Rafał Zdunek Шун-ичи Амари	2
+	Tensor decompositions for learning latent variable models	2014	Animashree Anandkumar Rong Ge Daniel Hsu Sham M. Kakade Matus Telgarsky	2
+	Fast algorithm for the solution of large‐scale non‐negativity‐constrained least squares problems	2004	Mark Hilary Van Benthem Michael R. Keenan	2
+ PDF Chat	Hierarchical Singular Value Decomposition of Tensors	2010	Lars Grasedyck	2
+ PDF Chat	Faster least squares approximation	2010	Petros Drineas Michael W. Mahoney S. Muthukrishnan Tamás Sarlós	2
+ PDF Chat	A Practical Randomized CP Tensor Decomposition	2018	Casey Battaglino Grey Ballard Tamara G. Kolda	2
+ PDF Chat	Algorithms for nonnegative matrix and tensor factorizations: a unified view based on block coordinate descent framework	2013	Jingu Kim Yunlong He Haesun Park	2
+	A comparison of algorithms for fitting the PARAFAC model	2004	Giorgio Tomasi Rasmus Bro	2
+	Fast Alternating LS Algorithms for High Order CANDECOMP/PARAFAC Tensor Factorizations	2013	Anh Huy Phan Petr Tichavský Andrzej Cichocki	2
+	Large Batch Training of Convolutional Networks	2017	Yang You Igor Gitman Boris Ginsburg	2
+	ChainerMN: Scalable Distributed Deep Learning Framework	2017	Takuya Akiba Keisuke Fukuda Shuji Suzuki	2
+	A high-performance parallel algorithm for nonnegative matrix factorization	2016	Ramakrishnan Kannan Grey Ballard Haesun Park	2
+	PARAFAC algorithms for large-scale problems	2011	Anh Huy Phan Andrzej Cichocki	2
+	Application of Deep Convolutional Neural Networks for Detecting Extreme Weather in Climate Datasets	2016	Yunjie Liu Evan Racah Prabhat Joaquin Correa Amir Khosrowshahi David A. Lavers Kenneth E. Kunkel Michael Wehner William D. Collins	2
+	Tensor Decomposition for Signal Processing and Machine Learning	2017	Nicholas D. Sidiropoulos Lieven De Lathauwer Xiao Fu Kejun Huang Evangelos E. Papalexakis Christos Faloutsos	2
+ PDF Chat	High Performance Parallel Algorithms for the Tucker Decomposition of Sparse Tensors	2016	Oguz Kaya Bora Uçar	2
+	MPI-FAUN: An MPI-Based Framework for Alternating-Updating Nonnegative Matrix Factorization	2017	Ramakrishnan Kannan Grey Ballard Haesun Park	2
+	Efficient and scalable computations with sparse tensors	2012	Muthu Manikandan Baskaran Benoît Meister Nicolas Vasilache Richard Lethin	2
+	PL-NMF: Parallel Locality-Optimized Non-negative Matrix Factorization	2019	Gordon Euhyun Moon Aravind Sukumaran-Rajam Srinivasan Parthasarathy P. Sadayappan	2
+ PDF Chat	Deep neural networks to enable real-time multimessenger astrophysics	2018	Daniel George E. A. Huerta	2
+ PDF Chat	A Comprehensive Physics-Informed Machine Learning Framework for Predictive Turbulence Modeling	2017	Jianxun Wang Jinlong Wu Julia Ling Gianluca Iaccarino Heng Xiao	2
+ PDF Chat	Interior-Point Gradient Method for Large-Scale Totally Nonnegative Least Squares Problems	2005	Michael Merritt Y. Zhang	2
+	Lat-Net: Compressing Lattice Boltzmann Flow Simulations using Deep Neural Networks	2017	Oliver Hennigh	2
+	Practical Bayesian Optimization of Machine Learning Algorithms	2012	Jasper Snoek Hugo Larochelle Ryan P. Adams	1
+ PDF Chat	Finding Structure with Randomness: Probabilistic Algorithms for Constructing Approximate Matrix Decompositions	2011	Nathan Halko Per‐Gunnar Martinsson Joel A. Tropp	1
+ PDF Chat	Efficient MATLAB Computations with Sparse and Factored Tensors	2007	Brett W. Bader Tamara G. Kolda	1