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