Xavier Hinaut – Towards interactive models with Reservoir Computing
03/12/2021, 15:00 (GMT+1, Warsaw)
Online Meeting
Please contact hill@hill.psych.uw.edu.pl to get access to the Zoom meeting.
We have the pleasure to announce a guest lecture by Dr. Xavier Hinaut. Dr. Hinaut will tell us about his recent work on language learning using reservoir computing.
Dr. Xavier Hinaut
INRIA National Institute for Research in Digital Science and Technology
Before the lecture, please read the first two publications listed in the Literature section (the third one is optional). If you want to better understand the subject of reservoir computing, there are additional materials, suggested by Dr. Hinaut.
Literature:
- Cross-situational learning:
Juven, A., & Hinaut, X. (2020). Cross-situational learning with reservoir computing for language acquisition modelling. - Birdsong model: Pagliarini, S., Leblois, A., & Hinaut, X. (2021). Canary Vocal Sensorimotor Model with RNN Decoder and Low-dimensional GAN Generator
- Additionally: Hinaut, X. & Dominey, PF. (2013). Real-time parallel processing of grammatical structure in the fronto-striatal system: A recurrent network simulation study using reservoir computing.
Additional information about Reservoir Computing:
- A quick overview:
Echo state network article on Scholarpedia - A tutorial about implementation:
Lukoševičius, M. (2012). A practical guide to applying echo state networks. - An online algorithm with chaotic reservoirs (that also work with non chaotic reservoir) which has a nice description for pattern generation:
Sussillo, D., & Abbott, LF. (2009). Generating coherent patterns of activity from chaotic neural networks.