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11/01/2021
Numerical Approximation in CFD Problems Using Physics Informed Machine Learning
The thesis focuses on various techniques to find an alternate approximat...
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08/14/2020
Abstracting Deep Neural Networks into Concept Graphs for Concept Level Interpretability
The black-box nature of deep learning models prevents them from being co...
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01/01/2020
A Generalized Deep Learning Framework for Whole-Slide Image Segmentation and Analysis
Histopathology tissue analysis is considered the gold standard in cancer...
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11/19/2019
Modelling pressure-Hessian from local velocity gradients information in an incompressible turbulent flow field using deep neural networks
The understanding of the dynamics of the velocity gradients in turbulent...
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07/21/2019
Distributed physics informed neural network for data-efficient solution to partial differential equations
The physics informed neural network (PINN) is evolving as a viable metho...
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07/08/2019
Physics Informed Extreme Learning Machine (PIELM) -- A rapid method for the numerical solution of partial differential equations
There has been rapid progress recently on the application of deep networ...
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11/16/2017