Learning in the Absence of Training Data

Dalia Chakrabarty ()
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Dalia Chakrabarty: Brunel University London, Department of Mathematics

in Springer Books from Springer

Date: 2023
ISBN: 978-3-031-31011-9
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Chapters in this book:

Ch Chapter 1 Bespoke Learning to Generate Originally-Absent Training Data

Dalia Chakrabarty

Ch Chapter 2 Learning the Temporally-Evolving Evolution-Driving Function of a Dynamical System, to Forecast Future States: Forecasting New COVID19 Infection Numbers

Dalia Chakrabarty

Ch Chapter 3 Potential to Density via Poisson Equation: Application to Bespoke Learning of Gravitational Mass Density in Real Galaxy

Dalia Chakrabarty

Ch Chapter 4 Bespoke Learning in Static Systems: Application to Learning Sub-surface Material Density Function

Dalia Chakrabarty

Ch Chapter 5 Bespoke Learning of Disease Progression Using Inter-Network Distance: Application to Haematology-Oncology: Joint Work with Dr. Kangrui Wang, Dr. Akash Bhojgaria and Dr. Joydeep Chakrabartty

Dalia Chakrabarty

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DOI: 10.1007/978-3-031-31011-9

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