An elegant PyTorch deep reinforcement learning library.

Software design principles for machine learning applications

pyDVL is a library of stable implementations of algorithms for data valuation and influence function computation

The Python library for sensible AI.

Learning function operators with neural networks.

A library for calibrating classifiers and computing calibration metrics

Normalizing flows for neuro-symbolic AI

Repository for the main part of the Machine Learning Control Training https://aai-institute.github.io/tfl-training-machine-learning-control

Repository of the Tranferlab Practical Anomaly Detection workshop

Code for the submission to the ML Reproducibility Challenge 2022, reproducing "If you like Shapley then you'll love the core"

Fork of ProtoTrees: Neural Prototype Trees for Interpretable Fine-grained Image Recognition, published at CVPR2021

TeXmacs plugin for TransferLab contributions

The pyDVL slides for pyData Berlin 2024

Repository of the appliedAI Institute TransferLab training "Simulation-Based Inference"

Experiments for the paper "Class-wise and reduced calibration methods", ICMLA 2022

Code for the reproduction of Class-wise Shapley paper from Schoch, Xu, Ji [2022].

An elegant PyTorch deep reinforcement learning library.

TfL course on probabilistic model checking using storm

Repository with material for the RL workshop at TUM.AI