v1v2 (latest)

Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data

27 December 2016

Anuj Karpatne

Papers citing "Theory-guided Data Science: A New Paradigm for Scientific Discovery from Data"

22 / 122 papers shown

Title
Enhancing streamflow forecast and extracting insights using long-short term memory networks with data integration at continental scales D. Feng K. Fang Chaopeng Shen AI4TS 91 282 0 18 Dec 2019
Physics-Guided Architecture (PGA) of Neural Networks for Quantifying Uncertainty in Lake Temperature Modeling Arka Daw R. Q. Thomas C. Carey J. Read A. Appling Anuj Karpatne AI4CE 83 120 0 06 Nov 2019
Physics-guided Design and Learning of Neural Networks for Predicting Drag Force on Particle Suspensions in Moving Fluids Nikhil Muralidhar Jie Bu Z. Cao Longting He Naren Ramakrishnan D. Tafti Anuj Karpatne DiffM PINN AI4CE 37 14 0 06 Nov 2019
Deep Learning of Subsurface Flow via Theory-guided Neural Network Nanzhe Wang Dongxiao Zhang Haibin Chang Heng Li AI4CE 109 235 0 24 Oct 2019
Explainable Artificial Intelligence (XAI): Concepts, Taxonomies, Opportunities and Challenges toward Responsible AI Alejandro Barredo Arrieta Natalia Díaz Rodríguez Javier Del Ser Adrien Bennetot Siham Tabik ... S. Gil-Lopez Daniel Molina Richard Benjamins Raja Chatila Francisco Herrera XAI 311 6,387 0 22 Oct 2019
Extracting Interpretable Physical Parameters from Spatiotemporal Systems using Unsupervised Learning Peter Y. Lu Samuel Kim Marin Soljacic AI4CE 58 60 0 13 Jul 2019
Explainable Machine Learning for Scientific Insights and Discoveries R. Roscher B. Bohn Marco F. Duarte Jochen Garcke XAI 120 677 0 21 May 2019
Enforcing Statistical Constraints in Generative Adversarial Networks for Modeling Chaotic Dynamical Systems Jin-Long Wu K. Kashinath A. Albert D. Chirila P. Prabhat Heng Xiao AI4CE 66 134 0 13 May 2019
Visualizing the Consequences of Climate Change Using Cycle-Consistent Adversarial Networks Victor Schmidt A. Luccioni S. Mukkavilli Narmada M. Balasooriya Kris Sankaran J. Chayes Yoshua Bengio GAN 45 38 0 02 May 2019
Applying machine learning to improve simulations of a chaotic dynamical system using empirical error correction P. Watson AI4Cl AI4CE 67 65 0 24 Apr 2019
DeepMoD: Deep learning for Model Discovery in noisy data G. Both Subham Choudhury P. Sens R. Kusters 96 116 0 20 Apr 2019
Informed Machine Learning -- A Taxonomy and Survey of Integrating Knowledge into Learning Systems Laura von Rueden S. Mayer Katharina Beckh B. Georgiev Sven Giesselbach ... Rajkumar Ramamurthy Michal Walczak Jochen Garcke Christian Bauckhage Jannis Schuecker 157 655 0 29 Mar 2019
Learning Everywhere: Pervasive Machine Learning for Effective High-Performance Computation Geoffrey C. Fox J. Glazier J. Kadupitiya V. Jadhao Minje Kim ... Madhav Marathe Abhijin Adiga Jiangzhuo Chen O. Beckstein S. Jha 59 53 0 27 Feb 2019
Combining Physically-Based Modeling and Deep Learning for Fusing GRACE Satellite Data: Can We Learn from Mismatch? A. Sun B. Scanlon Zizhan Zhang David Walling S. Bhanja A. Mukherjee Zhi Zhong AI4Cl 54 143 0 31 Jan 2019
An overview of deep learning in medical imaging focusing on MRI A. Lundervold A. Lundervold OOD 112 1,655 0 25 Nov 2018
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles X. Jia J. Willard Anuj Karpatne J. Read Jacob Aaron Zwart M. Steinbach Vipin Kumar PINN AI4CE 55 214 0 31 Oct 2018
Interpreting recurrent neural networks behaviour via excitable network attractors Andrea Ceni Peter Ashwin L. Livi 130 49 0 27 Jul 2018
A Spectral Approach for the Design of Experiments: Design, Analysis and Algorithms B. Kailkhura Jayaraman J. Thiagarajan Charvi Rastogi P. Varshney P. Bremer 48 20 0 16 Dec 2017
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 230 702 0 06 Dec 2017
Spatio-Temporal Data Mining: A Survey of Problems and Methods G. Atluri Anuj Karpatne Vipin Kumar AI4TS 63 275 0 13 Nov 2017
"Dave...I can assure you...that it's going to be all right..." -- A definition, case for, and survey of algorithmic assurances in human-autonomy trust relationships Brett W. Israelsen Nisar R. Ahmed 70 86 0 08 Nov 2017
Physics-guided Neural Networks (PGNN): An Application in Lake Temperature Modeling Arka Daw Anuj Karpatne William Watkins J. Read Vipin Kumar PINN 88 537 0 31 Oct 2017