We present Fortuna, an open-source library for uncertainty quantification in deep learning. Fortuna supports a range of calibration techniques, such as conformal prediction that can be applied to any trained neural network to generate reliable uncertainty estimates, and scalable Bayesian inference methods that can be applied to Flax-based deep neural networks trained from scratch for improved uncertainty quantification and accuracy. By providing a coherent framework for advanced uncertainty quantification methods, Fortuna simplifies the process of benchmarking and helps practitioners build robust AI systems.
TorchCP: A Python Library for Conformal Prediction
Southern University of Science and Technology（南方科技大学）；Nanyang Technological University（南洋理工大学）；Nanjing University（南京大学）；The Chinese University of Hong Kong, Shenzhen（香港中文大学（深圳））
dashi: A Python library for Dataset Shift Characterization to Support Trustworthy AI Development and Deployment
Biomedical Data Science Lab, Instituto Universitario de Tecnologías de la Información y Comunicaciones, Universitat Politècnica de Valéncia（生物医学数据科学实验室，信息与通信技术大学，巴塞罗那理工大学）
Uncertainty quantification in model discovery by distilling interpretable material constitutive models from Gaussian process posteriors
Technische Universität Braunschweig, Institute of Applied Mechanics（Braunschweig 技术大学应用力学研究所）；Technische Universität Braunschweig, Institute for Acoustics（Braunschweig 技术大学声学研究所）
Laplace Redux -- Effortless Bayesian Deep Learning
University of Cambridge（剑桥大学）；MPI for Intelligent Systems（马克斯·普朗克智能系统研究所）；University of Tübingen（蒂宾根大学）；ETH Zurich（苏黎世联邦理工学院）；Max Planck ETH Center for Learning Systems（马克斯·普朗克-苏黎世联邦理工学院学习系统中心）；DeepMind（深度思维）
Vine Copulas as Differentiable Computational Graphs
National University of Singapore（新加坡国立大学）；University of Applied Sciences Western Switzerland (HES-SO)（瑞士西部应用科学与艺术大学）；LMU Munich（慕尼黑大学）；Munich Center for Machine Learning（慕尼黑机器学习中心）
GAUCHE: A Library for Gaussian Processes in Chemistry
University of Cambridge（剑桥大学）；University of Oxford（牛津大学）；Secondmind Labs（Secondmind实验室）；Stanford University（斯坦福大学）；Genentech（基因泰克）；University of Toronto（多伦多大学）；Vector Institute（向量研究所）；EPFL（洛桑联邦理工学院）；Cornell University（康奈尔大学）；Washington State University（华盛顿州立大学）；King’s College London（伦敦国王学院）；University College London（伦敦大学学院）；Evonik Industries AG（赢创工业集团）；Syracuse University（雪城大学）；IST Austria（奥地利科学技术研究所）；MILA Quebec AI Institute（魁北克人工智能研究所MILA）；HEC Montreal（蒙特利尔高等商学院）
UR2M: Uncertainty and Resource-Aware Event Detection on Microcontrollers
University of Cambridge（剑桥大学）；Singapore Management University（新加坡管理大学）；Cardiff University（卡迪夫大学）；Nokia Bell Labs（诺基亚贝尔实验室）；University of Colorado Boulder（科罗拉多大学博尔德分校）
TabPFN Extensions for Interpretable Geotechnical Modelling
Department of Civil and Environmental Engineering, Tohoku University（东北大学土木环境工程系）；Research Organization of Information and Systems, The Institute of Statistical Mathematics（信息与系统研究所统计数学研究所）；Department of Statistical Science, The Graduate University for Advanced Studies（高级研究大学统计科学系）
