Sl.No Chapter Name MP4 Download
1Introduction to inverse problemsDownload
2Fermi estimationDownload
3Forward/Direct and Inverse problemsDownload
4Key drivers for studying inverse methods in engineeringDownload
5Formulation for inverse problemsDownload
6Statistical tools for estimationDownload
7Statistical description of errorsDownload
8Well-posed and ill-posed problemsDownload
9Probability and Statistics Brief over view-IDownload
10Probability and Statistics Brief over view-IIDownload
11Gaussian distributionDownload
12Gaussian distribution (Contd.), and Maximum Likelihood Estimation (MLE)Download
13Linear least square regressionDownload
14Linear least square regression (contd.).Download
15Alternatives to Linear least square.Download
16Polynomial regressionDownload
17Inverse problems in transient conduction-IDownload
18Inverse problems in transient conduction-IIDownload
19Non-linear regressionDownload
20Gauss-Newton algorithm (GNA)Download
21Gauss-Newton algorithm (GNA) Example.Download
22Levenberg-Marquardt algorithm (LMA)Download
23Tikhonov regularizationDownload
24Jacobian and its calculationDownload
25Bayesian methodsDownload
26Bayesian methods contd..,Download
27Metropolis-Hastings algorithm (MH) and Markov Chain Monte Carlo Methods (MCMC)Download
28Introduction to machine learning in heat transferDownload
29Overview of machine learningDownload
30Calculation in a neural network modelDownload
31Gradient Descent methodDownload
32Gradient Descent method contd..,Download
33Back propagationDownload
34Neural network as a surrogate forward modelDownload
35PINN for an inverse problemDownload
36PINN for an inverse problem contd..,Download
37Inverse methods in heat transfer -SummaryDownload

Sl.No Chapter Name English
1Introduction to inverse problemsPDF unavailable
2Fermi estimationPDF unavailable
3Forward/Direct and Inverse problemsPDF unavailable
4Key drivers for studying inverse methods in engineeringPDF unavailable
5Formulation for inverse problemsPDF unavailable
6Statistical tools for estimationPDF unavailable
7Statistical description of errorsPDF unavailable
8Well-posed and ill-posed problemsPDF unavailable
9Probability and Statistics Brief over view-IPDF unavailable
10Probability and Statistics Brief over view-IIPDF unavailable
11Gaussian distributionPDF unavailable
12Gaussian distribution (Contd.), and Maximum Likelihood Estimation (MLE)PDF unavailable
13Linear least square regressionPDF unavailable
14Linear least square regression (contd.).PDF unavailable
15Alternatives to Linear least square.PDF unavailable
16Polynomial regressionPDF unavailable
17Inverse problems in transient conduction-IPDF unavailable
18Inverse problems in transient conduction-IIPDF unavailable
19Non-linear regressionPDF unavailable
20Gauss-Newton algorithm (GNA)PDF unavailable
21Gauss-Newton algorithm (GNA) Example.PDF unavailable
22Levenberg-Marquardt algorithm (LMA)PDF unavailable
23Tikhonov regularizationPDF unavailable
24Jacobian and its calculationPDF unavailable
25Bayesian methodsPDF unavailable
26Bayesian methods contd..,PDF unavailable
27Metropolis-Hastings algorithm (MH) and Markov Chain Monte Carlo Methods (MCMC)PDF unavailable
28Introduction to machine learning in heat transferPDF unavailable
29Overview of machine learningPDF unavailable
30Calculation in a neural network modelPDF unavailable
31Gradient Descent methodPDF unavailable
32Gradient Descent method contd..,PDF unavailable
33Back propagationPDF unavailable
34Neural network as a surrogate forward modelPDF unavailable
35PINN for an inverse problemPDF unavailable
36PINN for an inverse problem contd..,PDF unavailable
37Inverse methods in heat transfer -SummaryPDF unavailable


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