This folder contains reproduction of some results from the literature, using ReservoirPy's tools.
A notebook presenting Intrinsic Plasticity mechanism applied to Reservoirs, as presented by Schrauwen et al. in 20081 and Triesch in 20052.
A notebook presenting Non-linear Vector AutoRegressive machines, a particular flavor of Reservoir, as introduced by Gauthier, Bollt and Griffith in 20213.
This notebook is work-in-progress about the work from Asabuki, Hiratani and Fukai about unsupervised chunking of timeseries, presented in 20184.
Contributions are welcome! If you reproduced some important results from the literature using ReservoirPy, do not hesitate to submit a pull request, we will be happy to count you as a contributor to ReservoirPy.
These reproductions may not be complete or follow exactly the original paper or implementation. They are simply provided as demonstration of RC techniques and ReservoirPy capacities.
Schrauwen, B., Wardermann, M., Verstraeten, D., Steil, J. J., & Stroobandt, D. (2008). Improving reservoirs using intrinsic plasticity. Neurocomputing, 71(7), 1159–1171. https://doi.org/10.1016/j.neucom.2007.12.020↩
Triesch, J. (2005). A Gradient Rule for the Plasticity of a Neuron’s Intrinsic Excitability. In W. Duch, J. Kacprzyk, E. Oja, & S. Zadrożny (Eds.), Artificial Neural Networks: Biological Inspirations – ICANN 2005 (pp. 65–70). Springer. https://doi.org/10.1007/11550822_11↩
Gauthier, D. J., Bollt, E., Griffith, A., & Barbosa, W. A. S. (2021). Next generation reservoir computing. Nature Communications, 12(1), 5564. https://doi.org/10.1038/s41467-021-25801-2↩
Asabuki, T., Hiratani, N., & Fukai, T. (2018). Interactive reservoir computing for chunking information streams. PLOS Computational Biology, 14(10), e1006400. https://doi.org/10.1371/journal.pcbi.1006400↩