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ORCIDReese E. Jones
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2020 – today
- 2024
[i14]Jeremiah Hauth, Cosmin Safta, Xun Huan, Ravi G. Patel, Reese E. Jones:
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes. CoRR abs/2402.11179 (2024)- [i13]Ravi G. Patel, Cosmin Safta, Reese E. Jones:
Equivariant graph convolutional neural networks for the representation of homogenized anisotropic microstructural mechanical response. CoRR abs/2404.17584 (2024) - [i12]Govinda Anantha Padmanabha, Jan Niklas Fuhg, Cosmin Safta, Reese E. Jones, Nikolaos Bouklas:
Improving the performance of Stein variational inference through extreme sparsification of physically-constrained neural network models. CoRR abs/2407.00761 (2024) - 2023
- [i11]Wyatt Bridgman, Reese E. Jones, Mohammad Khalil:
Robust scalable initialization for Bayesian variational inference with multi-modal Laplace approximations. CoRR abs/2307.06424 (2023) - [i10]Jan Niklas Fuhg, Nikolaos Bouklas
, Reese E. Jones:
Stress representations for tensor basis neural networks: alternative formulations to Finger-Rivlin-Ericksen. CoRR abs/2308.11080 (2023) - [i9]Jan Niklas Fuhg, Reese E. Jones, Nikolaos Bouklas:
Extreme sparsification of physics-augmented neural networks for interpretable model discovery in mechanics. CoRR abs/2310.03652 (2023) - [i8]Saibal De, Reese E. Jones, Hemanth Kolla:
Accurate Data-Driven Surrogates of Dynamical Systems for Forward Propagation of Uncertainty. CoRR abs/2310.10831 (2023) - [i7]Wyatt Bridgman, Uma Balakrishnan, Reese E. Jones, Jiefu Chen, Xuqing Wu, Cosmin Safta, Yueqin Huang, Mohammad Khalil:
Enhancing Polynomial Chaos Expansion Based Surrogate Modeling using a Novel Probabilistic Transfer Learning Strategy. CoRR abs/2312.04648 (2023) - 2022
- [i6]Wyatt Bridgman, Xiaoxuan Zhang, Gregory H. Teichert, Mohammad Khalil, Krishna C. Garikipati, Reese E. Jones:
A heteroencoder architecture for prediction of failure locations in porous metals using variational inference. CoRR abs/2202.00078 (2022) - [i5]Rubén Villarreal, Nikolaos N. Vlassis, Nhon N. Phan, Tommie A. Catanach, Reese E. Jones, Nathaniel A. Trask, Sharlotte L. B. Kramer, WaiChing Sun:
Design of experiments for the calibration of history-dependent models via deep reinforcement learning and an enhanced Kalman filter. CoRR abs/2209.13126 (2022) - [i4]Reese E. Jones, Cosmin Safta, Ari Frankel:
Deep learning and multi-level featurization of graph representations of microstructural data. CoRR abs/2210.00854 (2022) - [i3]Jan Niklas Fuhg, Craig M. Hamel, Kyle Johnson, Reese E. Jones, Nikolaos Bouklas:
Modular machine learning-based elastoplasticity: generalization in the context of limited data. CoRR abs/2210.08343 (2022) - 2021
- [i2]Ari Frankel, Cosmin Safta, Coleman Alleman, Reese E. Jones:
Mesh-based graph convolutional neural network models of processes with complex initial states. CoRR abs/2107.00090 (2021) - 2020
- [j5]Ari Frankel, Kousuke Tachida, Reese E. Jones:
Prediction of the evolution of the stress field of polycrystals undergoing elastic-plastic deformation with a hybrid neural network model. Mach. Learn. Sci. Technol. 1(3): 35005 (2020)
2010 – 2019
- 2019
- [i1]Ari Frankel, Reese E. Jones, Laura P. Swiler:
Tensor Basis Gaussian Process Models of Hyperelastic Materials. CoRR abs/1912.10872 (2019) - 2016
- [j4]Julia Ling, Reese E. Jones, Jeremy A. Templeton:
Machine learning strategies for systems with invariance properties. J. Comput. Phys. 318: 22-35 (2016) - 2015
- [j3]Maher Salloum, Khachik Sargsyan, Reese E. Jones, Habib N. Najm, Bert J. Debusschere:
Quantifying Sampling Noise and Parametric Uncertainty in Atomistic-to-Continuum Simulations Using Surrogate Models. Multiscale Model. Simul. 13(3): 953-976 (2015) - 2012
- [j2]Maher Salloum, Khachik Sargsyan, Reese E. Jones, Bert J. Debusschere, Habib N. Najm, Helgi Adalsteinsson:
A Stochastic Multiscale Coupling Scheme to Account for Sampling Noise in Atomistic-to-Continuum Simulations. Multiscale Model. Simul. 10(2): 550-584 (2012) - 2010
- [j1]Jonathan A. Zimmerman, Reese E. Jones, Jeremy A. Templeton:
A material frame approach for evaluating continuum variables in atomistic simulations. J. Comput. Phys. 229(6): 2364-2389 (2010)
Coauthor Index
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