Welcome to ContinualAI Wiki¶
Humans have the extraordinary ability to learn continually from experience. Not only can we apply previously learned knowledge and skills to new situations, we can also use these as the foundation for later learning. One of the grand goals of AI is building an artificial “Continual Learning” agent that constructs a sophisticated understanding of the world from its own experience through the autonomous incremental development of ever more complex skills and knowledge.
The aim of ContinualAI Wiki is to create an open-source, collaborative wiki to provide a starting point for researchers, developers and AI enthusiasts who share an interest in Continual Learning and are willing to learn more or contribute to this field. Join us now and help us improving it and keeping it up to date!
Contents:
- Introduction
- Research
- Publications
- Applications
- Architectural Methods
- Benchmarks
- Bioinspired Methods
- Catastrophic Forgetting Studies
- Classics
- Continual Few Shot Learning
- Continual Meta Learning
- Continual Reinforcement Learning
- Continual Sequential Learning
- Dissertation and Theses
- Generative Replay Methods
- Hybrid Methods
- Meta Continual Learning
- Metrics and Evaluations
- Neuroscience
- Others
- Regularization Methods
- Rehearsal Methods
- Review Papers and Books
- Robotics
- Conference Workshops
- Research Programs
- Publications
- Industry
- Software and Benchmarks
- Tutorials and Courses
- Media Articles
- About Us
- GitHub