Francesco Martinuzzi
I’m a postdoc at the Max Planck Institute for the Physics of Complex Systems in Dresden, with research interests in machine learning, chaos, and nonlinear time series. My current work focuses on using ML to forecast chaotic dynamics.
I’ve been a Julia user since 2019 and have contributed to the ecosystem with packages like ReservoirComputing.jl and CellularAutomata.jl.
You can find out more about my work on my website.
Session
Recurrent neural networks (RNNs) are deep learning (DL) models for sequential data, with many variants developed over the last two decades. However, core DL libraries typically offer only a limited number of cell implementations. In this talk, I introduce RecurrentLayers.jl and LuxRecurrentLayers.jl, two libraries that extend Flux and Lux with over 30 additional RNN cells each, enabling broader experimentation and research.