Simulation By Deep Neural Operator (DeepONets)
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Section 1: Introduction

lecture 1: Introduction
lecture 2: Install PyTorch / CUDA
lecture 3: Course structure
lecture 4: Deep Neural Operator
Ref.txt
Section 2: Pytorch Basics

Section-2 Files
lecture 5: Deep Learning Theory
lecture 6: PyTorch Tensors Basics
lecture 7: Tensors to NumPy arrays
lecture 8: Backpropagation Theory
lecture 9: Backpropagation using PyTorch
Section 3: FDM Numerical Solution 1D Heat Equation

Section-3 Files
lecture 10: Numerical solution theory
lecture 11: Pre-processing
lecture 12: Solving the Equation
lecture 13: Post-processing
Section 4: ODE Integration Neural Operator using PyTorch

Section-4 Files
lecture 14: Data creation
lecture 15: Data Preprocessing - Part 1
lecture 16: Data Preprocessing - Part 2
lecture 17: Model Build Up
lecture 18: Training Process
lecture 19: Results Evaluation
Section 5: 1D Heat Equation Neural Operator using PyTorch

Section-5 Files
lecture 20: Data creation
lecture 21: Data Preprocessing - Part 1
lecture 22: Data Preprocessing - Part 2
lecture 23: Model Build Up
lecture 24: Training Process
lecture 25: Results Evaluation
Section 6: 1D Heat Equation Neural Operator using DeepXDE

Section-6 Files
lecture 26: Data creation
lecture 27: Data Preprocessing
lecture 28: Model Build Up
lecture 29: Training Process
lecture 30: Results Evaluation
Section 7: 2D Fluid Neural Operator using DeepXDE

Section-7 Files
lecture 31: Data creation
lecture 32: Data Preprocessing
lecture 33: Model Build Up
lecture 34: Training Process
lecture 35: Results Evaluation

lecture 8: Backpropagation Theory

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