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A PyTorch library for implementing flow matching algorithms, featuring continuous and discrete flow matching implementations. It includes practical examples for both text and image modalities.
Repository for CARTE: Context-Aware Representation of Table Entries
Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.
Lecture notes, tutorial tasks including solutions as well as online videos for the reinforcement learning course hosted by Paderborn University
A fast and flexible implementation of Rigid Body Dynamics algorithms and their analytical derivatives
tsl: a PyTorch library for processing spatiotemporal data.
Pretrain, finetune ANY AI model of ANY size on multiple GPUs, TPUs with zero code changes.
ALICE (Automated Learning and Intelligence for Causation and Economics) is a Microsoft Research project aimed at applying Artificial Intelligence concepts to economic decision making. One of its go…
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphic…
PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.
HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.
A package for statistically rigorous scientific discovery using machine learning. Implements prediction-powered inference.
Making your benchmark of optimization algorithms simple and open
Statsmodels: statistical modeling and econometrics in Python
A Python Package to Tackle the Curse of Imbalanced Datasets in Machine Learning
Domain adaptation toolbox compatible with scikit-learn and pytorch
A unified framework for machine learning with time series
A high-performance implementation of Wilkinson formulas for Python.
Stan development repository. The master branch contains the current release. The develop branch contains the latest stable development. See the Developer Process Wiki for details.
Bayesian Modeling and Probabilistic Programming in Python
A Python package to learn the Koopman operator.
Up-to-date version of labs for ISLP
scikit-learn: machine learning in Python
A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.
Python programs, usually short, of considerable difficulty, to perfect particular skills.