Ali Can Bekar

According to our database, Ali Can Bekar authored at least 8 papers between 2020 and 2025.

Collaborative distances:

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

2025

Physics-based machine learning for mantle convection simulations.

Siddhant Agarwal, Ali Can Bekar, Christian Hüttig, David S. Greenberg, Nicola Tosi

CoRR, May, 2025

Multiphysics discovery with moving boundaries using Ensemble SINDy and peridynamic differential operator.

Ali Can Bekar, Ehsan Haghighat, Erdogan Madenci

Eng. Comput., April, 2025

2024

Accelerating the discovery of steady-states of planetary interior dynamics with machine learning.

Siddhant Agarwal, Nicola Tosi, Christian Hüttig, David S. Greenberg, Ali Can Bekar

CoRR, 2024

2023

Nonlocal Physics Informed Machine Learning Algorithms Using Peridynamic Differential Operator.

Ali Can Bekar

PhD thesis, 2023

2022

An unsupervised latent/output physics-informed convolutional-LSTM network for solving partial differential equations using peridynamic differential operator.

A. Mavi, Ali Can Bekar, Ehsan Haghighat, Erdogan Madenci

CoRR, 2022

2021

Peridynamics enabled learning partial differential equations.

Ali Can Bekar, Erdogan Madenci

J. Comput. Phys., 2021

Deep learning for solution and inversion of structural mechanics and vibrations.

Ehsan Haghighat, Ali Can Bekar, Erdogan Madenci, Ruben Juanes

CoRR, 2021

2020

A nonlocal physics-informed deep learning framework using the peridynamic differential operator.

Ehsan Haghighat, Ali Can Bekar, Erdogan Madenci, Ruben Juanes

CoRR, 2020