Mamikon A. Gulian

According to our database, Mamikon A. Gulian authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Stratospheric aerosol source inversion: Noise, variability, and uncertainty quantification.

Joseph L. Hart, Indu Manickam, Mamikon A. Gulian, Laura P. Swiler, Diana Bull, T. Ehrmann, H. Brown, B. Wagman, Jerry Watkins

CoRR, 2024

2023

Solving High-Dimensional Inverse Problems with Auxiliary Uncertainty via Operator Learning with Limited Data.

Joseph L. Hart, Mamikon A. Gulian, Indu Manickam, Laura P. Swiler

CoRR, 2023

2022

Error-in-variables modelling for operator learning.

Ravi G. Patel, Indu Manickam, Myoungkyu Lee, Mamikon A. Gulian

Proceedings of the Mathematical and Scientific Machine Learning, 2022

2021

Probabilistic partition of unity networks: clustering based deep approximation.

Nathaniel Trask, Mamikon A. Gulian, Andy Huang, Kookjin Lee

CoRR, 2021

Analysis of Anisotropic Nonlocal Diffusion Models: Well-posedness of Fractional Problems for Anomalous Transport.

Marta D'Elia, Mamikon A. Gulian

CoRR, 2021

A Block Coordinate Descent Optimizer for Classification Problems Exploiting Convexity.

Ravi G. Patel, Nathaniel Trask, Mamikon A. Gulian, Eric C. Cyr

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

Partition of Unity Networks: Deep HP-Approximation.

Kookjin Lee, Nathaniel Trask, Ravi G. Patel, Mamikon A. Gulian, Eric C. Cyr

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2020

What is the fractional Laplacian? A comparative review with new results.

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

J. Comput. Phys., 2020

Gaussian Process Regression constrained by Boundary Value Problems.

Mamikon A. Gulian, Ari Frankel, Laura P. Swiler

CoRR, 2020

A Survey of Constrained Gaussian Process Regression: Approaches and Implementation Challenges.

Laura P. Swiler, Mamikon A. Gulian, Ari Frankel, Cosmin Safta, John D. Jakeman

CoRR, 2020

Data-driven learning of robust nonlocal physics from high-fidelity synthetic data.

Huaiqian You, Yue Yu, Nathaniel Trask, Mamikon A. Gulian, Marta D'Elia

CoRR, 2020

Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint.

Eric C. Cyr, Mamikon A. Gulian, Ravi G. Patel, Mauro Perego, Nathaniel A. Trask

Proceedings of Mathematical and Scientific Machine Learning, 2020

2019

Machine Learning of Space-Fractional Differential Equations.

Mamikon A. Gulian, Maziar Raissi, Paris Perdikaris, George E. Karniadakis

SIAM J. Sci. Comput., 2019