MLOSS 2022

16 papers

Abess: A Fast Best-Subset Selection Library in Python and R Jin Zhu, Xueqin Wang, Liyuan Hu, Junhao Huang, Kangkang Jiang, Yanhang Zhang, Shiyun Lin, Junxian Zhu

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CleanRL: High-Quality Single-File Implementations of Deep Reinforcement Learning Algorithms Shengyi Huang, Rousslan Fernand Julien Dossa, Chang Ye, Jeff Braga, Dipam Chakraborty, Kinal Mehta, João G.M. Araújo

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D3rlpy: An Offline Deep Reinforcement Learning Library Takuma Seno, Michita Imai

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Darts: User-Friendly Modern Machine Learning for Time Series Julien Herzen, Francesco Lässig, Samuele Giuliano Piazzetta, Thomas Neuer, Léo Tafti, Guillaume Raille, Tomas Van Pottelbergh, Marek Pasieka, Andrzej Skrodzki, Nicolas Huguenin, Maxime Dumonal, Jan Kościsz, Dennis Bader, Frédérick Gusset, Mounir Benheddi, Camila Williamson, Michal Kosinski, Matej Petrik, Gaël Grosch

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Deepchecks: A Library for Testing and Validating Machine Learning Models and Data Shir Chorev, Philip Tannor, Dan Ben Israel, Noam Bressler, Itay Gabbay, Nir Hutnik, Jonatan Liberman, Matan Perlmutter, Yurii Romanyshyn, Lior Rokach

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DoubleML - An Object-Oriented Implementation of Double Machine Learning in Python Philipp Bach, Victor Chernozhukov, Malte S. Kurz, Martin Spindler

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InterpretDL: Explaining Deep Models in PaddlePaddle Xuhong Li, Haoyi Xiong, Xingjian Li, Xuanyu Wu, Zeyu Chen, Dejing Dou

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JsonGrinder.jl: Automated Differentiable Neural Architecture for Embedding Arbitrary JSON Data Šimon Mandlík, Matěj Račinský, Viliam Lisý, Tomáš Pevný

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Ktrain: A Low-Code Library for Augmented Machine Learning Arun S. Maiya

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OMLT: Optimization & Machine Learning Toolkit Francesco Ceccon, Jordan Jalving, Joshua Haddad, Alexander Thebelt, Calvin Tsay, Carl D Laird, Ruth Misener

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ReservoirComputing.jl: An Efficient and Modular Library for Reservoir Computing Models Francesco Martinuzzi, Chris Rackauckas, Anas Abdelrehim, Miguel D. Mahecha, Karin Mora

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SMAC3: A Versatile Bayesian Optimization Package for Hyperparameter Optimization Marius Lindauer, Katharina Eggensperger, Matthias Feurer, André Biedenkapp, Difan Deng, Carolin Benjamins, Tim Ruhkopf, René Sass, Frank Hutter

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Solo-Learn: A Library of Self-Supervised Methods for Visual Representation Learning Victor Guilherme Turrisi da Costa, Enrico Fini, Moin Nabi, Nicu Sebe, Elisa Ricci

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Tianshou: A Highly Modularized Deep Reinforcement Learning Library Jiayi Weng, Huayu Chen, Dong Yan, Kaichao You, Alexis Duburcq, Minghao Zhang, Yi Su, Hang Su, Jun Zhu

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Toolbox for Multimodal Learn (scikit-Multimodallearn) Dominique Benielli, Baptiste Bauvin, Sokol Koço, Riikka Huusari, Cécile Capponi, Hachem Kadri, François Laviolette

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WarpDrive: Fast End-to-End Deep Multi-Agent Reinforcement Learning on a GPU Tian Lan, Sunil Srinivasa, Huan Wang, Stephan Zheng

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