An elegant PyTorch deep reinforcement learning library.
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Updated
May 11, 2024 - Python
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.
A library for calibrating classifiers and computing calibration metrics
Learning function operators with neural networks.
Normalizing flows for neuro-symbolic AI
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
The pyDVL slides for pyData Berlin 2024
TeXmacs plugin for TransferLab contributions
Experiments for the paper "Class-wise and reduced calibration methods", ICMLA 2022
TfL course on probabilistic model checking using storm
Repository with material for the RL workshop at TUM.AI
An elegant PyTorch deep reinforcement learning library.
A fork of the anomalib library for research purposes
Algorithms for data valuation and benchmarks
Domain specific language for configuration spaces in Python/Cython. Useful for hyperparameter optimization and algorithm configuration.
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