Gaussian processes: from theory to applications
Pulicati, Leonardo (A.A. 2024/2025) Gaussian processes: from theory to applications. Tesi di Laurea in Advanced statistics, Luiss Guido Carli, relatore Marta Catalano, pp. 83. [Master's Degree Thesis]
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Abstract/Index
Overview on gaussian processes. Gaussian processes regression. The regression problem. Frequentist linear regression. Bayesian linear regression. Gaussian processes regression. Bayesian linear regression vs gaussian processes regression. Hyperparameters. Equivalent kernel. Basis functions. Real World Case. Gaussian processes classification. General framework for classification. Linear models for classification with Bayesian inference (Bayesian logistic regression). Gaussian processes classification. Gaussian processes classification: multiclass Laplace approximation. Simulation-based calibration for validating gaussian processes inference. Simulation-based calibration for gaussian processes. SBC evaluation in gaussian processes regression and classification. SBC in gaussian processes regression. SBC in gaussian processes classification.
References
Bibliografia: p. 83.
| Thesis Type: | Master's Degree Thesis |
|---|---|
| Institution: | Luiss Guido Carli |
| Degree Program: | Master's Degree Programs > Master's Degree Program in Data Science e Management (LM-91) |
| Chair: | Advanced statistics |
| Thesis Supervisor: | Catalano, Marta |
| Thesis Co-Supervisor: | Martino, Alessio |
| Academic Year: | 2024/2025 |
| Session: | Autumn |
| Deposited by: | Alessandro Perfetti |
| Date Deposited: | 03 Mar 2026 10:59 |
| Last Modified: | 03 Mar 2026 10:59 |
| URI: | https://tesi.luiss.it/id/eprint/45046 |
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