Shaoming Xu

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All published works
Action Title Year Authors
+ PDF Chat Hierarchical Conditional Multi-Task Learning for Streamflow Modeling 2024 Shaoming Xu
Arvind Renganathan
Ankush Khandelwal
Rahul Ghosh
Xiang Li
Licheng Liu
Kshitij Tayal
Peter de B. Harrington
Xiaowei Jia
Zhenong Jin
+ PDF Chat Kilometer-Scale Convection Allowing Model Emulation using Generative Diffusion Modeling 2024 Jaideep Pathak
Yair Cohen
Piyush Garg
Peter Harrington
Noah Brenowitz
Dale R. Durran
Morteza Mardani
Arash Vahdat
Shaoming Xu
Karthik Kashinath
+ PDF Chat Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling 2024 Shaoming Xu
Ankush Khandelwal
Arvind Renganathan
Vipin Kumar
+ PDF Chat Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications 2023 Shaoming Xu
Ankush Khandelwal
Xiang Li
Xiaowei Jia
Licheng Liu
Jared Willard
Rahul Ghosh
Kelly Deits Cutler
Michael Steinbach
Christopher Duffy
+ Message Propagation Through Time: An Algorithm for Sequence Dependency Retention in Time Series Modeling 2023 Shaoming Xu
Ankush Khandelwal
Arvind Renganathan
Vipin Kumar
+ PDF Chat Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems 2022 Jared Willard
Xiaowei Jia
Shaoming Xu
Michael Steinbach
Vipin Kumar
+ Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications 2022 Shaoming Xu
Ankush Khandelwal
Xiang Li
Xiaowei Jia
Licheng Liu
Jared Willard
Rahul Ghosh
Kelly Deits Cutler
Michael Steinbach
Christopher Duffy
+ Physics Guided Machine Learning Methods for Hydrology. 2020 Ankush Khandelwal
Shaoming Xu
Xiang Li
Xiaowei Jia
Michael Steinbach
Christopher Duffy
John L. Nieber
Vipin Kumar
+ Integrating Physics-Based Modeling with Machine Learning: A Survey 2020 Jared Willard
Xiaowei Jia
Shaoming Xu
Michael Steinbach
Vipin Kumar
+ Physics-Guided Recurrent Graph Networks for Predicting Flow and Temperature in River Networks 2020 Xiaowei Jia
Jacob A. Zwart
Jeffrey M. Sadler
Alison Appling
Samantha K. Oliver
Steven L. Markstrom
Jared Willard
Shaoming Xu
Michael Steinbach
Jordan S. Read
+ Physics Guided Machine Learning Methods for Hydrology 2020 Ankush Khandelwal
Shaoming Xu
Xiang Li
Xiaowei Jia
Michael Stienbach
Christopher Duffy
John L. Nieber
Vipin Kumar
+ Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems 2020 Jared Willard
Xiaowei Jia
Shaoming Xu
Michael Steinbach
Vipin Kumar
Common Coauthors
Commonly Cited References
Action Title Year Authors # of times referenced
+ PDF Chat Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles 2019 Xiaowei Jia
Jared Willard
Anuj Karpatne
Jordan S. Read
Jacob A. Zwart
Michael Steinbach
Vipin Kumar
3
+ PDF Chat Physics-informed machine learning approach for reconstructing Reynolds stress modeling discrepancies based on DNS data 2017 Jianxun Wang
Jinlong Wu
Heng Xiao
3
+ Real-Time Power System State Estimation and Forecasting via Deep Unrolled Neural Networks 2019 Liang Zhang
Gang Wang
Georgios B. Giannakis
2
+ Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations 2018 Liu Yang
Dongkun Zhang
George Em Karniadakis
2
+ Reduced Order Methods for Modeling and Computational Reduction 2014 Alfio Quarteroni
Gianluigi Rozza
2
+ Discovering governing equations from data by sparse identification of nonlinear dynamical systems 2016 Steven L. Brunton
Joshua L. Proctor
J. Nathan Kutz
2
+ Weakly-Supervised Deep Learning of Heat Transport via Physics Informed Loss 2018 Rishi Sharma
Amir Barati Farimani
Joe Gomes
Peter Eastman
Vijay S. Pande
2
+ PDF Chat Prognostic Validation of a Neural Network Unified Physics Parameterization 2018 Noah Brenowitz
Christopher S. Bretherton
2
+ PDF Chat Deep learning of dynamics and signal-noise decomposition with time-stepping constraints 2019 Samuel Rudy
J. Nathan Kutz
Steven L. Brunton
2
+ PDF Chat Learning data-driven discretizations for partial differential equations 2019 Yohai Bar‐Sinai
Stephan Hoyer
Jason Hickey
Michael P. Brenner
2
+ PDF Chat Deep Residual Learning for Image Recognition 2016 Kaiming He
Xiangyu Zhang
Shaoqing Ren
Jian Sun
2
+ PDF Chat Geometric Deep Learning: Going beyond Euclidean data 2017 Michael M. Bronstein
Joan Bruna
Yann LeCun
Arthur Szlam
Pierre Vandergheynst
2
+ PDF Chat Accurate interatomic force fields via machine learning with covariant kernels 2017 Aldo Glielmo
Peter Sollich
Alessandro De Vita
2
+ PDF Chat Deep Convolutional Neural Network for Inverse Problems in Imaging 2017 Kyong Hwan Jin
Michael T. McCann
Emmanuel Froustey
Michaël Unser
2
+ PDF Chat Time-lagged autoencoders: Deep learning of slow collective variables for molecular kinetics 2018 Christoph Wehmeyer
Frank Noé
2
+ PDF Chat Hybrid modeling and prediction of dynamical systems 2017 Franz Hamilton
Alun L. Lloyd
Kevin Flores
2
+ PDF Chat Variational Koopman models: Slow collective variables and molecular kinetics from short off-equilibrium simulations 2017 Hao Wu
Feliks NĂŒske
Fabian Paul
Stefan Klus
PĂ©ter Koltai
Frank Noé
2
+ PDF Chat Machine learning for many-body physics: The case of the Anderson impurity model 2014 Louis-François Arsenault
Alejandro López‐Bezanilla
O. Anatole von Lilienfeld
Andrew J. Millis
2
+ PDF Chat Domain randomization for transferring deep neural networks from simulation to the real world 2017 Josh Tobin
Rachel Fong
Alex Ray
Jonas Schneider
Wojciech Zaremba
Pieter Abbeel
2
+ A Domain Guided CNN Architecture for Predicting Age from Structural Brain Images 2018 Pascal Sturmfels
Saige Rutherford
Mike Angstadt
Mark Peterson
Chandra Sripada
Jenna Wiens
2
+ PDF Chat Neural network closures for nonlinear model order reduction 2018 Omer San
Romit Maulik
2
+ BĂ©zierGAN: Automatic Generation of Smooth Curves from Interpretable Low-Dimensional Parameters 2018 Wei Chen
Mark Fuge
2
+ PDF Chat Data-driven discovery of partial differential equations 2017 Samuel Rudy
Steven L. Brunton
Joshua L. Proctor
J. Nathan Kutz
2
+ PDF Chat Deep Potential Molecular Dynamics: A Scalable Model with the Accuracy of Quantum Mechanics 2018 Linfeng Zhang
Jiequn Han
Han Wang
Roberto Car
E Weinan
2
+ Parametrization and generation of geological models with generative adversarial networks 2017 Shing Chan
Ahmed H. Elsheikh
2
+ Hidden physics models: Machine learning of nonlinear partial differential equations 2017 Maziar Raissi
George Em Karniadakis
2
+ DGM: A deep learning algorithm for solving partial differential equations 2018 Justin Sirignano
Konstantinos Spiliopoulos
2
+ DR-RNN: A deep residual recurrent neural network for model reduction 2017 J. Nagoor Kani
Ahmed H. Elsheikh
2
+ Deep Learning the Physics of Transport Phenomena 2017 Amir Barati Farimani
Joseph Gomes
Vijay S. Pande
2
+ PDF Chat Machine Learning Approximation Algorithms for High-Dimensional Fully Nonlinear Partial Differential Equations and Second-order Backward Stochastic Differential Equations 2019 Christian Beck
E Weinan
Arnulf Jentzen
2
+ PDF Chat Jet substructure classification in high-energy physics with deep neural networks 2016 Pierre Baldi
Kevin Thomas Bauer
Clara Eng
Peter Sadowski
D. Whiteson
2
+ HybridNet: Integrating Model-based and Data-driven Learning to Predict Evolution of Dynamical Systems 2018 Yun Long
Xueyuan She
Saibal Mukhopadhyay
2
+ PDF Chat Physics-Guided Neural Networks (PGNN): An Application in Lake Temperature Modeling 2022 Arka Daw
Anuj Karpatne
W D Watkins
Jordan S. Read
Vipin Kumar
2
+ PDF Chat Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network 2017 Hu Chen
Yi Zhang
Mannudeep K. Kalra
Feng Lin
Yang Chen
Peixi Liao
Jiliu Zhou
Ge Wang
2
+ PDF Chat The TensorMol-0.1 model chemistry: a neural network augmented with long-range physics 2018 Kun Yao
John E. Herr
David W. Toth
Ryker Mckintyre
John Parkhill
2
+ PDF Chat Joint Gaussian Processes for Biophysical Parameter Retrieval 2017 Daniel Heestermans Svendsen
Luca Martino
Manuel Campos‐Taberner
Francisco Javier Garcı́a-Haro
Gustau Camps‐Valls
2
+ Physics Informed Deep Learning (Part I): Data-driven Solutions of Nonlinear Partial Differential Equations 2017 Maziar Raissi
Paris Perdikaris
George Em Karniadakis
2
+ PDF Chat Deep learning for universal linear embeddings of nonlinear dynamics 2018 Bethany Lusch
J. Nathan Kutz
Steven L. Brunton
2
+ PDF Chat Bayesian deep convolutional encoder–decoder networks for surrogate modeling and uncertainty quantification 2018 Yinhao Zhu
Nicholas Zabaras
2
+ PDF Chat Quantifying Uncertainty in Discrete-Continuous and Skewed Data with Bayesian Deep Learning 2018 Thomas Vandal
Evan Kodra
Jennifer Dy
Sangram Ganguly
Ramakrishna Nemani
Auroop R. Ganguly
2
+ PDF Chat Deep UQ: Learning deep neural network surrogate models for high dimensional uncertainty quantification 2018 Rohit Tripathy
Ilias Bilionis
2
+ PDF Chat Solving the quantum many-body problem with artificial neural networks 2017 Giuseppe Carleo
Matthias Troyer
2
+ PDF Chat Physics-aware Gaussian processes in remote sensing 2018 Gustau Camps‐Valls
Luca Martino
Daniel Heestermans Svendsen
Manuel Campos‐Taberner
Jordi Muñoz-Marı́
Valero Laparra
David Luengo
Francisco Javier Garcı́a-Haro
2
+ PDF Chat Data-assisted reduced-order modeling of extreme events in complex dynamical systems 2018 Zhong Wan
Pantelis R. Vlachas
Petros Koumoutsakos
Themistoklis P. Sapsis
2
+ PDF Chat Extended dynamic mode decomposition with dictionary learning: A data-driven adaptive spectral decomposition of the Koopman operator 2017 Qianxiao Li
Felix Dietrich
Erik M. Bollt
Ioannis G. Kevrekidis
2
+ A Deep Learning based Approach to Reduced Order Modeling for Turbulent Flow Control using LSTM Neural Networks 2018 Arvind Mohan
Datta V. Gaitonde
2
+ Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data 2017 Anuj Karpatne
Gowtham Atluri
James H. Faghmous
Michael Steinbach
Arindam Banerjee
Auroop R. Ganguly
Shashi Shekhar
Nagiza Samatova
Vipin Kumar
2
+ Solving high-dimensional partial differential equations using deep learning 2018 Jiequn Han
Arnulf Jentzen
E Weinan
2
+ MolGAN: An implicit generative model for small molecular graphs 2018 Nicola De Cao
Thomas Kipf
2
+ Neural Architecture Search: A Survey 2018 Thomas Elsken
Jan Hendrik Metzen
Frank Hutter
2