FilippoMB/Time-series-classification-and-clustering-with-Reservoir-Computing
Implement Reservoir Computing models for time series classification, clustering, forecasting, and much more!
Repositories
FilippoMB/Diffusion_models_tutorial
Collection of tutorials on diffusion models, step-by-step implementation guide, scripts for generating images with AI, prompt engineering guide, and resources for further learning.
FilippoMB/coauthors-graph
FilippoMB/Physics-Informed-Neural-Networks-tutorial
Hands-on tutorial for implementing Physics Informed Neural Networks in Pytorch
FilippoMB/python-time-series-handbook
Book and material for the course "Time series analysis with Python" (STA-2003)
FilippoMB/The-expressive-power-of-pooling-in-GNNs
Code and dataset to test empirically the expressive power of graph pooling operators presented as presented at NeurIPS 2023
FilippoMB/Ensemble-Conformalized-Quantile-Regression
Valid and adaptive prediction intervals for probabilistic time series forecasting.
FilippoMB/ml-seminar-temporal-data
FilippoMB/Pyramidal-Reservoir-Graph-Neural-Networks
Official repository of the paper "Pyramidal Reservoir Graph Neural Networks".
FilippoMB/Spectral-Clustering-with-Graph-Neural-Networks-for-Graph-Pooling
Reproduces the results of MinCutPool as presented in the 2020 ICML paper "Spectral Clustering with Graph Neural Networks for Graph Pooling".
FilippoMB/Simplifying-Clustering-with-Graph-Neural-Networks
Implementation of "Just Balance GNN" for graph classification and node clustering from the paper "Simplifying Clusterings with Graph Neural Networks".
FilippoMB/NFR-funding-dashboard
FilippoMB/Time-Series-Cluster-Kernel
Kernel similarity for classification and clustering of multi-variate time series with missing values.
FilippoMB/pytorch_geometric
Graph Neural Network Library for PyTorch
FilippoMB/FilippoMB
FilippoMB/cross-validation-tutorial
Introduction to cross-valdation in Machine Learning, with coding examples for supervised classification.
FilippoMB/github-readme-stats-fmb
FilippoMB/github-readme-stats
:zap: Dynamically generated stats for your github readmes
FilippoMB/Benchmark_dataset_for_graph_classification
Dataset for testing graph classification algorithms, such as Graph Kernels and Graph Neural Networks.
FilippoMB/lecture_RNN_phase_space
FilippoMB/graph-pooling-papers
IJCAI‘23 Survey Track: Papers on Graph Pooling (GNN-Pooling)
FilippoMB/blogs
My clone repository
FilippoMB/Detecting-and-interpreting-faults-in-vulnerable-power-grids-with-machine-learning
Repository of the paper "Detecting and interpreting faults in vulnerable power grids with machine learning".
FilippoMB/Variational-Graph-Auto-encoders-Tensorflow-2-Spektral-
Implementation of the Variational Graph Auto-encoder in Spektral (Tensorflow-Keras)
FilippoMB/Total-variation-graph-neural-networks
Pytorch (PyG) and Tensorflow (Keras/Spektral) implementation of Total Variation Graph Neural Network (TVGNN), as presented at ICML 2023.
FilippoMB/Deep-Kernelized-Auto-Encoder-with-Time-series-Cluster-Kernel
implementation of a Deep Kernelized Auto Encoder for learning vectorial representations of mutlivariate time series with missing data.
FilippoMB/Autoencoder-Tensorflow
Tensorflow implementation of an AE. Multiple models can be handled and trained at the same time.
FilippoMB/Recognition-of-polar-lows-in-Sentinel-1-SAR-images-with-deep-learning
Code implementation for the paper "Recognition of polar lows in Sentinel-1 SAR images with deep learning".
FilippoMB/Learning-representations-for-multivariate-time-series-with-missing-data
Learns representations of time series with missing data with an autoencoder regularized by a time series kernel.
FilippoMB/Bidirectional-Deep-readout-Echo-State-Network
Multivariate time series classification with a bi-directional ESN with a deep neural network readout.