MLOSS 2021

18 papers

Alibi Explain: Algorithms for Explaining Machine Learning Models Janis Klaise, Arnaud Van Looveren, Giovanni Vacanti, Alexandru Coca

PDF Code

ChainerRL: A Deep Reinforcement Learning Library Yasuhiro Fujita, Prabhat Nagarajan, Toshiki Kataoka, Takahiro Ishikawa

PDF Code

Dalex: Responsible Machine Learning with Interactive Explainability and Fairness in Python Hubert Baniecki, Wojciech Kretowicz, Piotr Piątyszek, Jakub Wiśniewski, Przemysław Biecek

PDF Code

DIG: A Turnkey Library for Diving into Graph Deep Learning Research Meng Liu, Youzhi Luo, Limei Wang, Yaochen Xie, Hao Yuan, Shurui Gui, Haiyang Yu, Zhao Xu, Jingtun Zhang, Yi Liu, Keqiang Yan, Haoran Liu, Cong Fu, Bora M Oztekin, Xuan Zhang, Shuiwang Ji

PDF Code

FATE: An Industrial Grade Platform for Collaborative Learning with Data Protection Yang Liu, Tao Fan, Tianjian Chen, Qian Xu, Qiang Yang

PDF Code

Giotto-Tda: : A Topological Data Analysis Toolkit for Machine Learning and Data Exploration Guillaume Tauzin, Umberto Lupo, Lewis Tunstall, Julian Burella Pérez, Matteo Caorsi, Anibal M. Medina-Mardones, Alberto Dassatti, Kathryn Hess

PDF Code

Kernel Operations on the GPU, with Autodiff, Without Memory Overflows Benjamin Charlier, Jean Feydy, Joan Alexis Glaunès, François-David Collin, Ghislain Durif

PDF Code

Mlr3pipelines - Flexible Machine Learning Pipelines in R Martin Binder, Florian Pfisterer, Michel Lang, Lennart Schneider, Lars Kotthoff, Bernd Bischl

PDF Code

MushroomRL: Simplifying Reinforcement Learning Research Carlo D'Eramo, Davide Tateo, Andrea Bonarini, Marcello Restelli, Jan Peters

PDF Code

Mvlearn: Multiview Machine Learning in Python Ronan Perry, Gavin Mischler, Richard Guo, Theodore Lee, Alexander Chang, Arman Koul, Cameron Franz, Hugo Richard, Iain Carmichael, Pierre Ablin, Alexandre Gramfort, Joshua T. Vogelstein

PDF Code

OpenML-Python: An Extensible Python API for OpenML Matthias Feurer, Jan N. van Rijn, Arlind Kadra, Pieter Gijsbers, Neeratyoy Mallik, Sahithya Ravi, Andreas Müller, Joaquin Vanschoren, Frank Hutter

PDF Code

POT: Python Optimal Transport Rémi Flamary, Nicolas Courty, Alexandre Gramfort, Mokhtar Z. Alaya, Aurélie Boisbunon, Stanislas Chambon, Laetitia Chapel, Adrien Corenflos, Kilian Fatras, Nemo Fournier, Léo Gautheron, Nathalie T.H. Gayraud, Hicham Janati, Alain Rakotomamonjy, Ievgen Redko, Antoine Rolet, Antony Schutz, Vivien Seguy, Danica J. Sutherland, Romain Tavenard, Alexander Tong, Titouan Vayer

PDF Code

Pykg2vec: A Python Library for Knowledge Graph Embedding Shih-Yuan Yu, Sujit Rokka Chhetri, Arquimedes Canedo, Palash Goyal, Mohammad Abdullah Al Faruque

PDF Code

River: Machine Learning for Streaming Data in Python Jacob Montiel, Max Halford, Saulo Martiello Mastelini, Geoffrey Bolmier, Raphael Sourty, Robin Vaysse, Adil Zouitine, Heitor Murilo Gomes, Jesse Read, Talel Abdessalem, Albert Bifet

PDF Code

Sklvq: Scikit Learning Vector Quantization Rick van Veen, Michael Biehl, Gert-Jan de Vries

PDF Code

Stable-Baselines3: Reliable Reinforcement Learning Implementations Antonin Raffin, Ashley Hill, Adam Gleave, Anssi Kanervisto, Maximilian Ernestus, Noah Dormann

PDF Code

TensorHive: Management of Exclusive GPU Access for Distributed Machine Learning Workloads Paweł Rościszewski, Michał Martyniak, Filip Schodowski

PDF Code

The Ensmallen Library for Flexible Numerical Optimization Ryan R. Curtin, Marcus Edel, Rahul Ganesh Prabhu, Suryoday Basak, Zhihao Lou, Conrad Sanderson

PDF Code