Memory is the way we keep telling ourselves our stories...
We use tools from machine learning and statistics to figure out how learning and memory happen at the level of neural circuits.
Studying learning, in brains and machines.
Characterizing the statistics of neural activity patterns:
How do neurons work together to achieve circuit function?
How do their interactions change due to learning?
Recent focus: online learning in recurrent neural networks,
Febr '20 | Cristina receives Google faculty award (Kyunghyun Cho co-PI).
Jan '20 | Colin and David's work accepted at Cosyne!
Oct '19 | Owen and Colin to present their work in NeurIPS 2019 workshops.
Sept '19 | Caroline's paper accepted for the NeurIPS 2019 main meeting.
July '19 | Check out Owen's new paper on online training of recurrent networks!
May '19 | Caroline receives Google fellowship; Camille awarded an NSF GRFP.
Jan '19 | Four posters accepted to Cosyne!
Dec '18 | Eun Hye Park's paper on head direction coding published in Neuron.
July '18 | Paper on unsupervised learning in neural circuits published in Scientific Reports.
Sept '17 | New MaxEnt review published in Curr Opin Neurobiol.