Data-driven Learning of Nonlocal Models: from high-fidelity simulations to constitutive laws (English)
Free access
- New search for: You, Huaiqian
- New search for: Yu, Yue
- New search for: Silling, Stewart
- New search for: D'Elia, Marta
- New search for: You, Huaiqian
- New search for: Yu, Yue
- New search for: Silling, Stewart
- New search for: D'Elia, Marta
In:
AAAI-MLPS 2021: Combining Artificial Intelligence and Machine Learning with Physical Sciences
;
2021
- Conference paper / Electronic Resource
-
Title:Data-driven Learning of Nonlocal Models: from high-fidelity simulations to constitutive laws
-
Contributors:You, Huaiqian ( author ) / Yu, Yue ( author ) / Silling, Stewart ( author ) / D'Elia, Marta ( author )
-
Conference:AAAI Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physics Sciences ; 2021 ; Online
-
Published in:
-
Publisher:
- New search for: [RWTH Aachen]
-
Place of publication:[Aachen, Germany]
-
Publication date:2021
-
Type of media:Conference paper
-
Type of material:Electronic Resource
-
Language:English
-
Source:
The tables of contents are generated automatically and are based on the data records of the individual contributions available in the index of the TIB portal. The display of the Tables of Contents may therefore be incomplete.
-
Discovery of Physics and Characterization of Microstructure from Data with Bayesian Hidden Physics ModelsAtkinson, Steven / Zhang, Yiming / Wang, Liping et al. | 2021
-
Convolutional LSTM for Planetary Boundary Layer Height (PBLH) PredictionZiaei, Dorsa / Sleeman, Jennifer / Halem, Milton / Caicedo, Vanessa / Delgado, Ruben / Demoz, Belay et al. | 2021
-
Learning High-Dimensional Hilbert-Valued Functions With Deep Neural Networks From Limited DataAdcock, Ben / Brugiapaglia, Simone / Dexter, Nick / Moraga, Sebastian et al. | 2021
-
Model Reduction for the Material Point Method on Nonlinear Manifolds Using Deep LearningChen, Peter Yichen / Chiaramonte, Maurizio / Grinspun, Eitan / Carlberg, Kevin et al. | 2021
-
Sparsely Constrained Neural Networks for Model Discovery of PDEsBoth, Gert-Jan / Vermarien, Gijs / Kusters, Remy et al. | 2021
-
A Deep Learning Algorithm for Piecewise Linear Interface Construction (PLIC)Ataei, Mohammadmehdi / Pirmorad, Erfan / Costa, Franco / Han, Sejin / Park, Chul / Bussmann, Markus et al. | 2021
-
Combining Programmable Potentials and Neural Networks for Materials ProblemsMohr, Ryan / Avila, Allan / Gosh, Soham / Bhattarai, Ananta / Yang, Muqiao / Feng, Xintian / Head-Gordon, Martin / Salakhutdinov, Ruslan / Fonoberova, Maria / Mezic, Igor et al. | 2021
-
Extended Physics-informed Neural Networks (XPINNs): A Generalized Space-Time Domain Decomposition based Deep Learning Framework for Nonlinear Partial Differential EquationsJagtap, Ameya / Karniadakis, George et al. | 2021
-
Greedy Fiedler Spectral Partitioning for Data-driven Discrete Exterior CalculusHuang, Andy / Trask, Nathaniel / Brissette, Christopher / Hu, Xiaozhe et al. | 2021
-
Data-driven Learning of Nonlocal Models: from high-fidelity simulations to constitutive lawsYou, Huaiqian / Yu, Yue / Silling, Stewart / D'Elia, Marta et al. | 2021
-
Neural Ordinary Differential Equations for Data-Driven Reduced Order Modeling of Environmental HydrodynamicsDutta, Sourav / Rivera-Casillas, Peter / Farthing, Matthew et al. | 2021
-
Toward Geometrical Robustness with Hybrid Deep Learning and Differential Invariants TheoryLagrave, Pierre-Yves / Riou, Mathieu et al. | 2021
-
Physics Informed Deep Learning for Well Test AnalysisR, Balakrishna D. / Rathinasamy, Kamalkumar / Das, Avijit / Ashwin, Keerthi / Sivasankaran, Vani / Rajendran, Soundararajan et al. | 2021
-
Deep Autoencoders for Nonlinear Physics-Constrained Data-Driven Computational Framework with Application to Biological Tissue ModelingHe, Xiaolong / He, Qizhi / Chen, Jiun-Shyan et al. | 2021
-
Learning the Principle of Least Action with Reinforcement LearningJin, Zehao / Lin, Joshua Yao-Yu / Li, Siao-Fong et al. | 2021
-
Learning Physics-guided Neural Networks with Competing Physics Loss: A Summary of Results in Solving Eigenvalue ProblemsElhamod, Mohannad / Bu, Jie / Singh, Christopher / Redell, Matthew / Ghosh, Abantika / Podolskiy, Viktor / Lee, Wei-Cheng / Karpatne, Anuj et al. | 2021
-
Applications of Koopman Mode Analysis to Neural NetworksMohr, Ryan / Fonoberova, Maria / Manojlovic, Iva / Andrejcuk, Aleksandr / Drmac, Zlatko / Kevrekidis, Yannis / Mezic, Igor et al. | 2021
-
Modeling Physically-Consistent, Chaotic Spatiotemporal Dynamics with Echo State NetworksSharma, Alisha / Shi, Kaiyan / Qiao, Yiling / Ziemann, Matthew et al. | 2021
-
Physics-Informed Machine Learning Simulator for Wildfire PropagationBottero, Luca / Calisto, Francesco / Graziano, Giovanni / Pagliarino, Valerio / Scauda, Martina / Tiengo, Sara / Azeglio, Simone et al. | 2021
-
Reduced-order Model for Fluid Flows via Neural Ordinary Differential EquationsRojas, Carlos Jose Gonzalez / Dengel, Andreas / Ribeiro, Mateus Dias et al. | 2021
-
Physics-informed Neural Networks for Solving Coupled Flow and Transport SystemLee, Sanghyun / Kadeethum, Teeratorn et al. | 2021
-
Variational Autoencoders for Learning Nonlinear Dynamics of PDEs and ReductionsLopez, Ryan / Atzberger, Paul et al. | 2021
-
Learning Potentials of Quantum Systems using Deep Neural NetworksSehanobish, Arijit / Corzo, Hector / Kara, Onur / Dijk, David van et al. | 2021
-
Surrogate Modeling for Physical Systems with Preserved Properties and Adjustable TradeoffsWang, Randi / Behandish, Morad et al. | 2021
-
Accelerating High-fidelity Combustion Simulations with Classification AlgorithmsChung, Wai Tong / Mishra, Aashwin / Perakis, Nikolaos / Ihme, Matthias et al. | 2021
-
Accurate Machine Learning-based Diagnostic with Quantified UncertaintiesHanuka, Adi / Convery, Owen et al. | 2021
-
Data-based Discovery of Governing EquationsSubber, Waad / Pandita, Piyush / Ghosh, Sayan / Khan, Genghis / Wang, Liping / Ghanem, Roger et al. | 2021
-
A Block Coordinate Descent Optimizer for Classification Problems Exploiting ConvexityPatel, Ravi / Trask, Nathaniel / Gulian, Mamikon / Cyr, Eric et al. | 2021
-
AI Research Associate for Early-Stage Scientific DiscoveryBehandish, Morad / Maxwell, John / Kleer, Johan de et al. | 2021
-
Deep Learning-based Fast Solver of the Shallow Water EquationsForghani, Mojtaba / Qian, Yizhou / Lee, Jonghyun / Farthing, Matthew / Hesser, Tyler / Kitanidis, Peter / Darve, Eric et al. | 2021
-
Graph Networks with Physics-aware Knowledge Informed in Latent SpaceSeo, Sungyong / Liu, Yan et al. | 2021
-
Neural Process for Black-box Model Optimization Under Bayesian FrameworkShangguan, Zhongkai / Lin, Lei / Wu, Wencheng / Xu, Beilei et al. | 2021
-
TextureVAE: Learning Interpretable Representations of Material Microstructures Using Variational AutoencodersSardeshmukh, Avadhut / Reddy, Sreedhar / Gautham, Bp / Bhattacharyya, Pushpak et al. | 2021
-
LSTMs for Inferring Planetary Boundary Layer Height (PBLH)Ali, Zeenat / Ziaei, Dorsa / Sleeman, Jennifer / Yang, Zhifeng / Halem, Milton et al. | 2021
-
Learning Dynamical Systems across EnvironmentsYin, Yuan / Ayed, Ibrahim / Bézenac, Emmanuel de / Gallinari, Patrick et al. | 2021
-
Validation of Deep Convolutional Generative Adversarial Networks for High Energy Physics Calorimeter SimulationsRehm, Florian / Vallecorsa, Sofia / Borras, Kerstin / Krücker, Dirk et al. | 2021
-
Graph-Informed Neural NetworksTaverniers, Søren / Hall, Eric J. / Katsoulakis, Markos A. / Tartakovsky, Daniel M. et al. | 2021
-
Bayesian-Inference-based Inverse Estimation of Small Angle ScatteringAsahara, Akinori / Morita, Hidekazu / Ono, Kanta / Yano, Masao / Mitsumata, Chiharu / Shoji, Tetsuya / Saito, Kotaro et al. | 2021
-
ADCME MPI: Distributed Machine Learning for Computational EngineeringXu, Kailai / Darve, Eric et al. | 2021
-
MatVAE: Independently Trained Nested Variational Autoencoder for Generating Chemical Structural FormulaOsakabe, Yoshihiro / Asahara, Akinori et al. | 2021
-
Machine Learning Application for Permeability Estimation of Three-Dimensional Rock ImagesYoon, Hongkyu / Melander, Darryl / Verzi, Stephen et al. | 2021
-
Stiff-PINN: Physics-Informed Neural Network for Stiff Chemical KineticsJi, Weiqi / Qiu, Weilun / Shi, Zhiyu / Pan, Shaowu / Deng, Sili et al. | 2021
-
Data Driven Physics Constrained Perturbations for Turbulence Model Uncertainty EstimationHeyse, Jan Felix / Mishra, Aashwin Ananda / Iaccarino, Gianluca et al. | 2021
-
Generalized Physics-Informed Machine Learning for Transient Physical SystemsMeethal, Rishith Ellath / Kondamadugula, Leela Sai Prabhat Reddy / Khalil, Mohamed / Obst, Birgit / Wüchner, Roland et al. | 2021
-
Partition of Unity Networks: Deep HP-ApproximationLee, Kookjin / Trask, Nathaniel / Patel, Ravi / Gulian, Mamikon / Cyr, Eric et al. | 2021
-
Self-Adaptive Physics-Informed Neural Networks using a Soft Attention MechanismMcClenny, Levi / Braga-Neto, Ulisses et al. | 2021
-
Accelerating Simulation of Stiff Nonlinear Systems using Continuous-Time Echo State NetworksAnantharaman, Ranjan / Ma, Yingbo / Gowda, Shashi / Laughman, Chris / Shah, Viral / Edelman, Alan / Rackauckas, Chris et al. | 2021