ContinualAI Research (CLAIR) is a collaborative research team and observatory within ContinualAI with the goal of supporting the production, organization and dissemination of original research on CL and related topics.
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Mission
ContinualAI Research works mostly at a meta research level. Its core mission is to support the production, organization and dissemination of original research on CL with technical research, open source projects and tools that can make the life of a CL researcher easier. In particular, we would like to talk and propose practical solutions to the following questions among others:
- How can we help young researchers and enthustiasts in this area learn faster and be better supported by the community?
- How can we organize research in continual learning to make it easier to anyone find the right piece of information?
- How can we help continual learning researchers share more resources (insights, code and knowledge) and collaborate more together?
- How can we make continual learning research more accessible to anyone?
Projects
At the moment CLAIR is maintaining the following collaborative projects:
We are always looking for new CLAIR members! Write us a message on slack if you want to join us!
People
CLAIR is maintained by the following ContinualAI scientists:
Vincenzo Lomonaco
Director of Research & Chief Scientist
Neuroscience-inspired AI, Continual Learing, Robotics
vincenzo.lomonaco@continualai.org
German I. Parisi
Research Scientist
Neuroscience-inspired AI, Continual Learing, Robotics
german.parisi@continualai.org
Keiland Cooper
Research Scientist
Neuroscience, Neuroscience-inspired AI, Continual Learing
keiland.cooper@continualai.org
Qi She
Research Scientist
Continual Learing, Robotics
qi.she@continualai.org
Jeremy Forest
Research Scientist
Neuroscience, Neuroscience-inspired AI, Continual Learing
jeremy.forest@continualai.org