Notes
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A collection of fragments of understanding in the pursuit of deeper questions.
Contents
- Computational Vision
- Introduction to Data Science
- Translational Neuromodeling
- Deep Learning in Artificial & Biological Neuronal Networks
- Introduction to Neuroinformatics
- Intro to Neuroscience
- Systems Neuroscience
- Readings in Neuroinformatics
- Neurobiology of Consciousness
- Econometrics
- Principles of Finance
- Big Data & Databases
- Game Theory
- Intro to Blockchain
- Marketing Analytics
- Financial Accounting
- Fundamentals of Computer Science
- Foundamentals of Information Technology Law
- Statistics
- Computer Programming
- Macroeconomics
- EU Information Law & Data Economy
- Advanced Mathematics & Statistics
- Principles of Management
- Mathematics
- Microeconomics
Continual Learning - Introduction
Learning Arithmetics & Word Associations "Catastrophic interference in connectionist networks: the sequential learning problem". In front of a 2-task incremental learning scenario, Humans can still perform decently on the first task after having learned the second one, while neural nets immediately forget the first when they start learning the second.
In the picture we have the view of the parameter space.
Continual Learning "Scenarios" and Benchmarks There are three scenarios:
- Task-IL, solve tasks so far, task-ID provided.
- Domain-IL, solve tasks so far, task-ID not provided.
- Class-IL, solve tasks so far and infer task-ID.
