Prabhat

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All published works

Action	Title	Year	Authors
+	Learning from learning machines: a new generation of AI technology to meet the needs of science	2021	Luca Pion-Tonachini Kristofer E. Bouchard Héctor García Martín Sean Peisert W. Holtz Anil Aswani Dipankar Dwivedi Haruko Wainwright Ghanshyam Pilania Benjamin Nachman
+	Simulation of Lennard-Jones Potential on a Quantum Computer	2021	Prabhat Bikash K. Behera
+	Learning from learning machines: a new generation of AI technology to meet the needs of science	2021	Luca Pion-Tonachini Kristofer E. Bouchard Héctor García Martín Sean Peisert W. Holtz Anil Aswani Dipankar Dwivedi Haruko Wainwright Ghanshyam Pilania Benjamin Nachman
+	Track Seeding and Labelling with Embedded-space Graph Neural Networks.	2020	Nicholas Choma Daniel Murnane X. Ju P. Calafiura Sean Conlon Steven Farrell Prabhat G. B. Cerati Lindsey Gray T. Klijnsma
+	MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework	2020	Chiyu Max Jiang Soheil Esmaeilzadeh Kamyar Azizzadenesheli Karthik Kashinath Mustafa Mustafa Hamdi A. Tchelepi Philip Marcus Prabhat Anima Anandkumar
+	Graph Neural Networks for Particle Reconstruction in High Energy Physics detectors	2020	X. Ju Steven Farrell P. Calafiura Daniel Murnane Prabhat Lindsey Gray T. Klijnsma K. Pedro G. B. Cerati Jim Kowalkowski
+	MeshfreeFlowNet: A Physics-Constrained Deep Continuous Space-Time Super-Resolution Framework	2020	Chiyu Max Jiang Soheil Esmaeilzadeh Kamyar Azizzadenesheli Karthik Kashinath Mustafa Mustafa Hamdi A. Tchelepi Philip Marcus Prabhat Anima Anandkumar
+	Enforcing statistical constraints in generative adversarial networks for modeling chaotic dynamical systems	2019	Jinlong Wu Karthik Kashinath Adrian Albert Dragos B. Chirila Prabhat Heng Xiao
+	Etalumis	2019	Atılım Güneş Baydin Lei Shao W. Bhimji L. Heinrich Lawrence Meadows Jialin Liu Andreas Munk Saeid Naderiparizi Bradley Gram-Hansen Gilles Louppe
+	DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems	2019	Adam Rupe Nalini Kumar Vladislav Epifanov Karthik Kashinath Oleksandr Pavlyk F. Schlimbach Mostofa Patwary Sergey Maidanov Victor R. Lee Prabhat
+	Towards Unsupervised Segmentation of Extreme Weather Events	2019	Adam Rupe Karthik Kashinath Nalini Kumar Victor W. Lee Prabhat James P. Crutchfield
+	Approximate inference for constructing astronomical catalogs from images	2019	Jeffrey Regier Andrew C. Miller David J. Schlegel Ryan P. Adams Jon McAuliffe Prabhat
+	Deep Learning for Scientific Inference from Geophysical Data: The Madden-Julian Oscillation as a Test Case	2019	Benjamin A. Toms Karthik Kashinath Prabhat Da Yang
+	Spherical CNNs on Unstructured Grids	2019	Chiyu Max Jiang Jingwei Huang Karthik Kashinath Prabhat Philip Marcus Matthias Nießner
+	Spherical CNNs on Unstructured Grids	2019	Chiyu Max Jiang Jingwei Huang Karthik Kashinath Prabhat Philip Marcus Matthias Nießner
+	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model	2019	Atılım Güneş Baydin Lei Shao W. Bhimji L. Heinrich Saeid Naderiparizi Andreas Munk Jialin Liu Bradley Gram-Hansen Gilles Louppe Lawrence Meadows
+	Towards Unsupervised Segmentation of Extreme Weather Events	2019	Adam Rupe Karthik Kashinath Nalini Kumar Victor Lee Prabhat James P. Crutchfield
+	Highly-scalable, physics-informed GANs for learning solutions of stochastic PDEs	2019	Liu Yang Sean Treichler Thorsten Kurth Keno Fischer David A. Barajas‐Solano Josh Romero Valentin Churavy Alexandre M. Tartakovsky Michael Houston Prabhat
+	DisCo: Physics-Based Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems	2019	Adam Rupe Nalini Kumar Vladislav Epifanov Karthik Kashinath Oleksandr Pavlyk F. Schlimbach Mostofa Patwary Sergey Maidanov Victor Lee Prabhat
+	Spherical CNNs on Unstructured Grids	2019	Chiyu Jiang Jingwei Huang Karthik Kashinath Prabhat Philip Marcus Matthias Nießner
+	Testing the Reliability of Interpretable Neural Networks in Geoscience Using the Madden-Julian Oscillation	2019	Benjamin A. Toms Karthik Kashinath Prabhat Yang Da
+ PDF Chat	Alchemist: An Apache Spark ⇔ MPI interface	2018	Alex Gittens Kai Rothauge Shusen Wang Michael W. Mahoney Jey Kottalam L. Gerhardt Prabhat Michael Ringenburg Kristyn Maschhoff
+	Novel deep learning methods for track reconstruction	2018	Steven Farrell Mayur Mudigonda Paolo Calafiura Aristeidis Tsaris Jim Kowalkowski Lindsey Gray Panagiotis Spentzouris G. B. Cerati J. Bendavid Prabhat
+	Graph Neural Networks for IceCube Signal Classification	2018	Nicholas Choma Federico Monti L. Gerhardt Tomasz Jan Palczewski Zahra Ronaghi Prabhat W. Bhimji Michael M. Bronstein S. R. Klein Joan Bruna
+	Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC	2018	W. Bhimji Steven Farrell Thorsten Kurth M. Paganini Prabhat Evan Racah
+	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
+	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model	2018	Atılım Güneş Baydin L. Heinrich W. Bhimji Lei Shao Saeid Naderiparizi Andreas Munk Jialin Liu Bradley Gram-Hansen Gilles Louppe Lawrence Meadows
+	Accelerating Large-Scale Data Analysis by Offloading to High-Performance Computing Libraries using Alchemist	2018	Alex Gittens Kai Rothauge Shusen Wang Michael W. Mahoney L. Gerhardt Prabhat Jey Kottalam Michael Ringenburg Kristyn Maschhoff
+	Alchemist: An Apache Spark MPI Interface	2018	Alex Gittens Kai Rothauge Shusen Wang Michael W. Mahoney Jey Kottalam L. Gerhardt Prabhat Michael Ringenburg Kristyn Maschhoff
+ PDF Chat	Cataloging the Visible Universe Through Bayesian Inference at Petascale	2018	Jeffrey Regier Jon McAuliffe R. C. Thomas Prabhat Kiran Pamnany Keno Fischer Andreas Noack Maximilian Lam Jarrett Revels Steve Howard
+	Cataloging the Visible Universe through Bayesian Inference at Petascale	2018	Jeffrey Regier Kiran Pamnany Keno Fischer Andreas Noack Maximilian Lam Jarrett Revels Steve Howard Ryan Giordano David J. Schlegel Jon McAuliffe
+	Approximate Inference for Constructing Astronomical Catalogs from Images	2018	Jeffrey Regier Andrew C. Miller David J. Schlegel Ryan P. Adams Jon McAuliffe Prabhat
+	Optimizing the Union of Intersections LASSO ($UoI_{LASSO}$) and Vector Autoregressive ($UoI_{VAR}$) Algorithms for Improved Statistical Estimation at Scale	2018	Mahesh Balasubramanian Trevor Ruiz Brandon Cook Sharmodeep Bhattacharyya Prabhat Aviral Shrivastava Kristofer E. Bouchard
+	Novel deep learning methods for track reconstruction	2018	Steven Farrell P. Calafiura Mayur Mudigonda Prabhat Dustin Anderson Jean-Roch Vlimant Stephan Zheng J. Bendavid M. Spiropulu G. B. Cerati
+	Exascale Deep Learning for Climate Analytics	2018	Thorsten Kurth Sean Treichler Joshua Romero Mayur Mudigonda Nathan Luehr Everett C. Phillips A Mahesh Michael J. Matheson Jack Deslippe Massimiliano Fatica
+	Graph Neural Networks for IceCube Signal Classification	2018	Nicholas Choma Federico Monti L. Gerhardt Tomasz Jan Palczewski Zahra Ronaghi Prabhat W. Bhimji Michael M. Bronstein S. R. Klein Joan Bruna
+	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
+	Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model	2018	Atılım Güneş Baydin L. Heinrich W. Bhimji Lei Shao Saeid Naderiparizi Andreas Munk Jialin Liu Bradley Gram-Hansen Gilles Louppe Lawrence Meadows
+	Alchemist: An Apache Spark <=> MPI Interface	2018	Alex Gittens Kai Rothauge Shusen Wang Michael W. Mahoney Jey Kottalam L. Gerhardt Prabhat Michael Ringenburg Kristyn Maschhoff
+	Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer	2017	Amrita Mathuriya Thorsten Kurth Vivek Rane Mustafa Mustafa Lei Shao Debbie Bard Prabhat Victor W. Lee
+	Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC	2017	W. Bhimji Steven Farrell Thorsten Kurth M. Paganini Prabhat Evan Racah
+	Galactos	2017	Brian Friesen Md. Mostofa Ali Patwary Brian Austin Nadathur Satish Zachary Slepian Narayanan Sundaram Deborah Bard Daniel J. Eisenstein Jack Deslippe Pradeep Dubey
+	Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data	2017	Thorsten Kurth Jian Zhang Satish Nadathur Ioannis Mitliagkas Evan Racah Mostofa Patwary Tareq B. Malas Narayanan Sundaram W. Bhimji Mikhail E. Smorkalov
+	Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction	2017	Kristofer E. Bouchard Alejandro F. Bujan Farbod Roosta-Khorasani Shashanka Ubaru Prabhat Antoine M. Snijders Jian‐Hua Mao Edward F. Chang Michael W. Mahoney Sharmodeep Bhattacharyya
+	Semi-Supervised Detection of Extreme Weather Events in Large Climate Datasets	2017	Evan Racah Christopher Beckham Tegan Maharaj Prabhat Christopher Pal
+	ArrayBridge: Interweaving declarative array processing with high-performance computing	2017	Haoyuan Xing Sofoklis Floratos Spyros Blanas Suren Byna Prabhat Kesheng Wu Paul Brown
+	A Physics-Based Approach to Unsupervised Discovery of Coherent Structures in Spatiotemporal Systems	2017	Adam Rupe James P. Crutchfield Karthik Kashinath Prabhat
+	An Assessment of Data Transfer Performance for Large-Scale Climate Data Analysis and Recommendations for the Data Infrastructure for CMIP6	2017	Eli Dart Michael Wehner Prabhat
+	Improvements to Inference Compilation for Probabilistic Programming in Large-Scale Scientific Simulators	2017	Mario Lezcano Casado Atılım Güneş Baydin David Martínez-Rubio Tuan Anh Lê Frank Wood L. Heinrich Gilles Louppe K. Cranmer Karen Ng W. Bhimji
+	Scaling GRPC Tensorflow on 512 nodes of Cori Supercomputer	2017	Amrita Mathuriya Thorsten Kurth Vivek Rane Mustafa Mustafa Lei Shao Debbie Bard Prabhat Victor W. Lee
+	Deep Learning at 15PF: Supervised and Semi-Supervised Classification for Scientific Data	2017	Thorsten Kurth Jian Zhang Nadathur Satish Ioannis Mitliagkas Evan Racah Mostofa Patwary Tareq B. Malas Narayanan Sundaram W. Bhimji Mikhail E. Smorkalov
+	Union of Intersections (UoI) for Interpretable Data Driven Discovery and Prediction	2017	Kristofer E. Bouchard Alejandro F. Bujan Farbod Roosta-Khorasani Shashanka Ubaru Prabhat Antoine M. Snijders Jian‐Hua Mao Edward F. Chang Michael W. Mahoney Sharmodeep Bhattacharyya
+	Deep Neural Networks for Physics Analysis on low-level whole-detector data at the LHC	2017	W. Bhimji Steven Farrell Thorsten Kurth M. Paganini Prabhat Evan Racah
+	ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events	2016	Evan Racah Christopher Beckham Tegan Maharaj Samira Ebrahimi Kahou Prabhat Christopher Pal
+ PDF Chat	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks	2016	Evan Racah Seyoon Ko Peter Sadowski W. Bhimji C. E. Tull Sang‐Yun Oh Pierre Baldi Prabhat
+ PDF Chat	PANDA: Extreme Scale Parallel K-Nearest Neighbor on Distributed Architectures	2016	Md. Mostofa Ali Patwary Nadathur Satish Narayanan Sundaram Jialin Liu Peter Sadowski Evan Racah Suren Byna C. E. Tull W. Bhimji Prabhat
+	Revealing Fundamental Physics from the Daya Bay Neutrino Experiment Using Deep Neural Networks	2016	Evan Racah Seyoon Ko Peter Sadowski W. Bhimji C. E. Tull Sang‐Yun Oh Pierre Baldi Prabhat
+	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
+	Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies	2016	Alex Gittens Aditya Devarakonda Evan Racah Michael Ringenburg L. Gerhardt Jey Kottalam Jialin Liu Kristyn Maschhoff Shane Canon Jatin Chhugani
+	Learning an Astronomical Catalog of the Visible Universe through Scalable Bayesian Inference	2016	Jeffrey Regier Kiran Pamnany Ryan Giordano R. C. Thomas David J. Schlegel Jon McAuliffe Prabhat
+	ExtremeWeather: A large-scale climate dataset for semi-supervised detection, localization, and understanding of extreme weather events	2016	Evan Racah Christopher Beckham Tegan Maharaj Samira Ebrahimi Kahou Prabhat Christopher Pal
+	A Gaussian process model of quasar spectral energy distributions	2015	Andrew C. Miller Albert W. Wu Jeffrey Regier Jon McAuliffe Dustin Lang Prabhat David J. Schlegel Ryan P. Adams
+	Scalable Bayesian Optimization Using Deep Neural Networks	2015	Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros Nadathur Satish Narayanan Sundaram Md. Mostofa Ali Patwary Prabhat Ryan P. Adams
+	Scalable Bayesian Optimization Using Deep Neural Networks	2015	Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros Nadathur Satish Narayanan Sundaram Mostofa Patwary Prabhat Ryan P. Adams
+	Celeste: Variational inference for a generative model of astronomical images	2015	Jeffrey Regier Andrew C. Miller Jon McAuliffe Ryan P. Adams Matt Hoffman Dustin Lang David J. Schlegel Prabhat
+ PDF Chat	Parallelizing Gaussian Process Calculations in<i>R</i>	2015	Christopher J. Paciorek Benjamin Lipshitz Wei Zhuo Prabhat Cari G. Kaufman R. C. Thomas
+	ON SOME GENERALIZED DIFFERENCE PARANORMED SEQUENCE SPACES ASSOCIATED WITH MULTIPLIER SEQUENCE DEFINED BY MODULUS FUNCTION	2011	Binod Chandra Tripathy Prabhat

Common Coauthors

Coauthor	Papers Together
W. Bhimji	15
Karthik Kashinath	13
Evan Racah	13
Michael W. Mahoney	9
Thorsten Kurth	9
L. Gerhardt	7
David J. Schlegel	7
Jeffrey Regier	7
Steven Farrell	7
Jon McAuliffe	7
Lawrence Meadows	6
Nalini Kumar	6
Ryan P. Adams	6
Narayanan Sundaram	6
Jey Kottalam	5
Philip Marcus	5
Mostofa Patwary	5
Kristofer E. Bouchard	5
Atılım Güneş Baydin	5
Michael Ringenburg	5
Gilles Louppe	5
L. Heinrich	5
Kristyn Maschhoff	5
Adam Rupe	5
Alex Gittens	5
Nadathur Satish	5
James P. Crutchfield	5
Aristeidis Tsaris	4
Andrew C. Miller	4
K. Cranmer	4
Victor W. Lee	4
Victor C. S. Lee	4
Andreas Munk	4
Lindsey Gray	4
Saeid Naderiparizi	4
Jim Kowalkowski	4
Chiyu Max Jiang	4
R. C. Thomas	4
G. B. Cerati	4
M. Spiropulu	4
Frank Wood	4
Kai Rothauge	4
Panagiotis Spentzouris	4
Bradley Gram-Hansen	4
Jack Deslippe	4
Shusen Wang	4
Pradeep Dubey	4
Amrita Mathuriya	4
Jean-Roch Vlimant	4
L. Gray	4

Commonly Cited References

Action	Title	Year	Authors	# of times referenced
+	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	5
+	HOGWILD!: A Lock-Free Approach to Parallelizing Stochastic Gradient Descent	2011	Feng Niu Benjamin Recht Christopher Ré Stephen J. Wright	5
+ PDF Chat	Deep Residual Learning for Image Recognition	2016	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	5
+ PDF Chat	Jet-images — deep learning edition	2016	Luke de Oliveira M. Kagan Lester Mackey Benjamin Nachman A. Schwartzman	5
+	Stochastic variational inference	2013	Matthew D. Hoffman David M. Blei Chong Wang John Paisley	5
+ PDF Chat	Geometric Deep Learning: Going beyond Euclidean data	2017	Michael M. Bronstein Joan Bruna Yann LeCun Arthur Szlam Pierre Vandergheynst	4
+	Variational Inference: A Review for Statisticians	2017	David M. Blei Alp Kucukelbir Jon McAuliffe	4
+	Searching for exotic particles in high-energy physics with deep learning	2014	Pierre Baldi Peter Sadowski D. Whiteson	4
+	Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks	2015	Alec Radford Luke Metz Soumith Chintala	3
+	OverFeat: Integrated Recognition, Localization and Detection using Convolutional Networks	2014	Pierre Sermanet David Eigen Xiang Zhang Michaël Mathieu Rob Fergus Yann LeCun	3
+ PDF Chat	Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification	2015	Kaiming He Xiangyu Zhang Shaoqing Ren Jian Sun	3
+ PDF Chat	Computational Mechanics: Pattern and Prediction, Structure and Simplicity	2001	Cosma Rohilla Shalizi James P. Crutchfield	3
+	Stacked What-Where Auto-encoders	2015	Junbo Zhao Michaël Mathieu Ross Goroshin Yann LeCun	3
+ PDF Chat	Event generation with SHERPA 1.1	2009	T. Gleisberg Stefan Höche Frank Krauss Marek Schönherr S. Schumann F. Siegert Jan Winter	3
+	Matrix Factorization at Scale: a Comparison of Scientific Data Analytics in Spark and C+MPI Using Three Case Studies	2016	Alex Gittens Aditya Devarakonda Evan Racah Michael Ringenburg L. Gerhardt Jey Kottalam Jialin Liu Kristyn Maschhoff Shane Canon Jatin Chhugani	3
+ 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	3
+ PDF Chat	Building near-real-time processing pipelines with the spark-MPI platform	2017	N. Malitsky Aashish Chaudhary Sébastien Jourdain Matt Cowan Patrick O’Leary Marcus D. Hanwell Kerstin Kleese van Dam	3
+	Slice Sampling	2000	Radford M. Neal	3
+	Practical Bayesian Optimization of Machine Learning Algorithms	2012	Jasper Snoek Hugo Larochelle Ryan P. Adams	3
+ PDF Chat	Julia: A Fresh Approach to Numerical Computing	2017	Jeff Bezanson Alan Edelman Stefan Karpinski Viral B. Shah	3
+	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	3
+ PDF Chat	Reconstruction of hadronic decay products of tau leptons with the ATLAS experiment	2016	G. Aad B. Abbott J. Abdallah O. Abdinov R. Aben M. Abolins O. S. AbouZeid H. Abramowicz H. Abreu R. Abreu	2
+	FireCaffe: near-linear acceleration of deep neural network training on compute clusters	2015	Forrest Iandola Khalid Ashraf Mattthew W. Moskewicz Kurt Keutzer	2
+	Distributed Deep Learning Using Synchronous Stochastic Gradient Descent	2016	Dipankar Das Sasikanth Avancha Dheevatsa Mudigere Karthikeyan Vaidynathan Srinivas Sridharan Dhiraj Kalamkar Bharat Kaul Pradeep Dubey	2
+ PDF Chat	A brief introduction to PYTHIA 8.1	2008	Torbjörn Sjöstrand S. Mrenna Peter Skands	2
+ PDF Chat	The Sloan Digital Sky Survey: Technical Summary	2000	Donald G. York Jennifer Adelman John E. Anderson Scott F. Anderson James Annis Neta A. Bahcall Jon Arne Bakken Robert H. Barkhouser Steven Bastian Eileen Berman	2
+ PDF Chat	New Measurement of Antineutrino Oscillation with the Full Detector Configuration at Daya Bay	2015	Fengpeng An A. B. Balantekin H. R. Band M. Bishai S. Blyth Ilya Butorov G. F. Cao Jun Cao W. R. Cen Y. L. Chan	2
+ PDF Chat	Inference from Iterative Simulation Using Multiple Sequences	1992	Andrew Gelman Donald B. Rubin	2
+	LICORS: Light Cone Reconstruction of States for Non-parametric Forecasting of Spatio-Temporal Systems	2012	Georg M. Goerg Cosma Rohilla Shalizi	2
+	Network In Network	2013	Min Lin Qiang Chen Shuicheng Yan	2
+ PDF Chat	Dimensionality Reduction for Supervised Learning With Reproducing Kernel Hilbert Spaces	2003	Kenji Fukumizu Francis R. Bach Michael I. Jordan	2
+	Observation of a new boson at a mass of 125 GeV with the CMS experiment at the LHC	2012	S. Chatrchyan V. Khachatryan A. M. Sirunyan A. Tumasyan W. Adam E. Aguiló T. Bergauer M. Dragicevic J. Erö C. Fabjan	2
+	A guide to convolution arithmetic for deep learning	2016	Vincent Dumoulin Francesco Visin	2
+ PDF Chat	Fully convolutional networks for semantic segmentation	2015	Jonathan Long Evan Shelhamer Trevor Darrell	2
+ PDF Chat	ImageNet Large Scale Visual Recognition Challenge	2015	Olga Russakovsky Jia Deng Hao Su Jonathan Krause Sanjeev Satheesh Sean Ma Zhiheng Huang Andrej Karpathy Aditya Khosla Michael S. Bernstein	2
+	Statistical inference for stochastic simulation models - theory and application	2011	Florian Härtig Justin M. Calabrese Björn Reineking Thorsten Wiegand Andreas Huth	2
+	Reversible jump Markov chain Monte Carlo computation and Bayesian model determination	1995	Peter J. Green	2
+ PDF Chat	Optimization Under Unknown Constraints*	2011	Robert B. Gramacy Herbert K. H. Lee	2
+ PDF Chat	Optimal Nonlinear Prediction of Random Fields on Networks	2003	Cosma Rohilla Shalizi	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	Observation of Electron-Antineutrino Disappearance at Daya Bay	2012	Fengpeng An J. Z. Bai A. B. Balantekin H. R. Band D. Beavis W. Beriguete M. Bishai S. Blyth Kimberly K. Boddy Richard Brown	2
+	Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC	2012	G. Aad T. Abajyan B. Abbott J. Abdallah S. Abdel Khalek A. A. Abdelalim O. Abdinov R. Aben B. Abi M. Abolins	2
+ PDF Chat	CUR matrix decompositions for improved data analysis	2009	Michael W. Mahoney Petros Drineas	2
+ PDF Chat	Improved measurement of electron antineutrino disappearance at Daya Bay	2013	Fengpeng An Q. An J. Z. Bai A. B. Balantekin H. R. Band W. Beriguete M. Bishai S. Blyth Richard Brown G. F. Cao	2
+	Toward a quantitative theory of self-generated complexity	1986	Peter Grassberger	2
+ PDF Chat	Automatic filters for the detection of coherent structure in spatiotemporal systems	2006	Cosma Rohilla Shalizi Robert Haslinger Jean‐Baptiste Rouquier Kristina Lisa Klinkner Cristopher Moore	2
+	Improving neural networks by preventing co-adaptation of feature detectors	2012	Geoffrey E. Hinton Nitish Srivastava Alex Krizhevsky Ilya Sutskever Ruslan Salakhutdinov	2
+	None	2001	Radford M. Neal	2
+ PDF Chat	Search for a Light Sterile Neutrino at Daya Bay	2014	Fengpeng An A. B. Balantekin H. R. Band W. Beriguete M. Bishai S. Blyth Ilya Butorov G. F. Cao Jun Cao Y. L. Chan	2
+ PDF Chat	Spectroscopic Target Selection in the Sloan Digital Sky Survey: The Quasar Sample	2002	Gordon T. Richards Xiaohui Fan Heidi Jo Newberg Michael A. Strauss D. E. vanden Berk Donald P. Schneider B. Yanny Adam Boucher Scott Burles Joshua A. Frieman	2