Learning in the Absence of Training Data
This book introduces the concept of “bespoke learning”, a new mechanistic approach that makes it possible to generate values of an output variable at each designated value of an associated input variable. Here the output variable generally provides information about the system’s behaviour/structure,...
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| Format: | eBook |
| Language: | English |
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Cham
Springer International Publishing
2023, 2023
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| Edition: | 1st ed. 2023 |
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| Online Access: | |
| Collection: | Springer eBooks 2005- - Collection details see MPG.ReNa |
Table of Contents:
- 1 Bespoke Learning to generate originally-absent training data
- 2 Forecasting by Learning Evolution-Driver - Application to Forecasting New COVID19 Infections
- 3 Potential to Density - Application to Learning Galactic Gravitational Mass Density
- 4 Bespoke Learning in Static Systems - Application to Learning Sub-surface Material Density Function
- 5 Bespoke Learning of Output using Inter-Network Distance - Application to Haematology-Oncology
- A Bayesian inference by posterior sampling using MCMC.