a python framework to build, learn and reason about probabilistic circuits and tensor networks

[NAACL 2021] Factual Probing Is [MASK]: Learning vs. Learning to Recall https://arxiv.org/abs/2104.05240

Mini site for the "Advanced probabilistic modeling: from generative to neuro-symbolic AI" course for PhD students at the Unvesity of Trento 23/24

Official repository of GLGExplainer (ICLR2023)

GraphXAI: Resource to support the development and evaluation of GNN explainers

Material for the hands-on tutorial on Graph Deep Learning held at the Alan Turing Institute

Repository of the paper "L2XGNN: Learning to Explain Graph Neural Networks", Giuseppe Serra and Mathias Niepert, Machine Learning Journal, 2024.

A Python package for analyzing and transforming neural latent spaces.

Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts

HGX is a multi-purpose, open-source Python library for higher-order network analysis

Graph Neural Network Library for PyTorch

Repository associated to the paper: "Explaining the Explainers in Graph Neural Networks: a Comparative Study"

Papers about explainability of GNNs

A multi-task learning approach to person re-identification and attribute recognition. Written in PyTorch, trained and evaluated on the Market-1501 dataset.

A set of algorithms for non-rigid tracking of multiple objects in videos from different domains.