MLOSS 2025

11 papers

BoFire: Bayesian Optimization Framework Intended for Real Experiments Johannes P. Dürholt, Thomas S. Asche, Johanna Kleinekorte, Gabriel Mancino-Ball, Benjamin Schiller, Simon Sung, Julian Keupp, Aaron Osburg, Toby Boyne, Ruth Misener, Rosona Eldred, Chrysoula Kappatou, Robert M. Lee, Dominik Linzner, Wagner Steuer Costa, David Walz, Niklas Wulkow, Behrang Shafei

Depyf: Open the Opaque Box of PyTorch Compiler for Machine Learning Researchers Kaichao You, Runsheng Bai, Meng Cao, Jianmin Wang, Ion Stoica, Mingsheng Long

GraphNeuralNetworks.jl: Deep Learning on Graphs with Julia Carlo Lucibello, Aurora Rossi

Gsplat: An Open-Source Library for Gaussian Splatting Vickie Ye, Ruilong Li, Justin Kerr, Matias Turkulainen, Brent Yi, Zhuoyang Pan, Otto Seiskari, Jianbo Ye, Jeffrey Hu, Matthew Tancik, Angjoo Kanazawa

Lightning UQ Box: Uncertainty Quantification for Neural Networks Nils Lehmann, Nina Maria Gottschling, Jakob Gawlikowski, Adam J. Stewart, Stefan Depeweg, Eric Nalisnick

Ontolearn---a Framework for Large-Scale OWL Class Expression Learning in Python Caglar Demir, Alkid Baci, N'Dah Jean Kouagou, Leonie Nora Sieger, Stefan Heindorf, Simon Bin, Lukas Blübaum, Alexander Bigerl, Axel-Cyrille Ngonga Ngomo

PFLlib: A Beginner-Friendly and Comprehensive Personalized Federated Learning Library and Benchmark Jianqing Zhang, Yang Liu, Yang Hua, Hao Wang, Tao Song, Zhengui Xue, Ruhui Ma, Jian Cao

Skglm: Improving Scikit-Learn for Regularized Generalized Linear Models Badr Moufad, Pierre-Antoine Bannier, Quentin Bertrand, Quentin Klopfenstein, Mathurin Massias

Talent: A Tabular Analytics and Learning Toolbox Si-Yang Liu, Hao-Run Cai, Qi-Le Zhou, Huai-Hong Yin, Tao Zhou, Jun-Peng Jiang, Han-Jia Ye

TorchCP: A Python Library for Conformal Prediction Jianguo Huang, Jianqing Song, Xuanning Zhou, Bingyi Jing, Hongxin Wei

WEFE: A Python Library for Measuring and Mitigating Bias in Word Embeddings Pablo Badilla, Felipe Bravo-Marquez, María José Zambrano, Jorge Pérez