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ORCIDMamikon A. Gulian
Person information
- affiliation: Sandia National Labs, Livermore, CA, USA
- affiliation: Sandia National Labs, Albuquerque, NM, USA
- affiliation (PhD 2018): Brown University, Providence, RI, USA
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2020 – today
- 2023
[i11]Joseph L. Hart, Mamikon A. Gulian, Indu Manickam, Laura P. Swiler:
Solving High-Dimensional Inverse Problems with Auxiliary Uncertainty via Operator Learning with Limited Data. CoRR abs/2303.11379 (2023)- 2022
- [c4]Ravi G. Patel, Indu Manickam, Myoungkyu Lee, Mamikon A. Gulian:
Error-in-variables modelling for operator learning. MSML 2022: 142-157 - [i10]Ravi G. Patel, Indu Manickam, Myoungkyu Lee, Mamikon A. Gulian:
Error-in-variables modelling for operator learning. CoRR abs/2204.10909 (2022) - 2021
- [c3]Kookjin Lee, Nathaniel Trask, Ravi G. Patel, Mamikon A. Gulian, Eric C. Cyr:
Partition of Unity Networks: Deep HP-Approximation. AAAI Spring Symposium: MLPS 2021 - [c2]Ravi G. Patel, Nathaniel Trask, Mamikon A. Gulian, Eric C. Cyr:
A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity. AAAI Spring Symposium: MLPS 2021 - [i9]Marta D'Elia, Mamikon A. Gulian:
Analysis of Anisotropic Nonlocal Diffusion Models: Well-posedness of Fractional Problems for Anomalous Transport. CoRR abs/2101.04289 (2021) - [i8]Kookjin Lee, Nathaniel A. Trask, Ravi G. Patel, Mamikon A. Gulian, Eric C. Cyr:
Partition of unity networks: deep hp-approximation. CoRR abs/2101.11256 (2021) - [i7]Nathaniel Trask, Mamikon A. Gulian, Andy Huang, Kookjin Lee:
Probabilistic partition of unity networks: clustering based deep approximation. CoRR abs/2107.03066 (2021) - 2020
- [j2]Anna Lischke, Guofei Pang
, Mamikon A. Gulian, Fangying Song, Christian Glusa, Xiaoning Zheng, Zhiping Mao, Wei Cai, Mark M. Meerschaert, Mark Ainsworth, George Em Karniadakis:
What is the fractional Laplacian? A comparative review with new results. J. Comput. Phys. 404 (2020) - [c1]Eric C. Cyr, Mamikon A. Gulian, Ravi G. Patel, Mauro Perego, Nathaniel A. Trask:
Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint. MSML 2020: 512-536 - [i6]Huaiqian You, Yue Yu, Nathaniel Trask, Mamikon A. Gulian, Marta D'Elia:
Data-driven learning of robust nonlocal physics from high-fidelity synthetic data. CoRR abs/2005.10076 (2020) - [i5]Laura P. Swiler, Mamikon A. Gulian, Ari Frankel, Cosmin Safta, John D. Jakeman:
A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges. CoRR abs/2006.09319 (2020) - [i4]Ravi G. Patel, Nathaniel A. Trask, Mamikon A. Gulian, Eric C. Cyr:
A block coordinate descent optimizer for classification problems exploiting convexity. CoRR abs/2006.10123 (2020) - [i3]Mamikon A. Gulian, Ari Frankel, Laura P. Swiler:
Gaussian Process Regression constrained by Boundary Value Problems. CoRR abs/2012.11857 (2020)
2010 – 2019
- 2019
- [j1]Mamikon A. Gulian, Maziar Raissi, Paris Perdikaris, George E. Karniadakis:
Machine Learning of Space-Fractional Differential Equations. SIAM J. Sci. Comput. 41(4): A2485-A2509 (2019) - [i2]Eric C. Cyr, Mamikon A. Gulian, Ravi G. Patel, Mauro Perego, Nathaniel A. Trask:
Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint. CoRR abs/1912.04862 (2019) - 2018
- [i1]Mamikon A. Gulian, Maziar Raissi, Paris Perdikaris, George E. Karniadakis:
Machine Learning of Space-Fractional Differential Equations. CoRR abs/1808.00931 (2018)
Coauthor Index
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