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Francesco Crecchi

Expert
@FrancescoCrecchi

AI Engineer, Ph.D.

Multiscale-Parametric-t-SNE. ESANN20 paper code repository. This package is a perplexity-free extension of Parametric t-SNE dimensionality reduction method implemented in `Keras` and compatible with `Scikit-learn`.

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DropIn-ESN. This repository contains the code used to produce the results presented in the IJCNN 2017 paper "DropIn: Making Reservoir Computing Neural Networks Robust to Missing Inputs by Dropout" by D. Bacciu, F. Crecchi (University of Pisa) and D. Morelli (Biobeats LTD).

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AE_Detector. Python

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Intro_Keras. Introduction to Keras deep learning framework.

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FADER. Fast Adversarial Examples Reject repository.

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DtNR. t-SNE based Deep Neural Rejection (DNR) repository.

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Classpad. Classpad

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