Machine Learning at Microsoft with ML.NET. - Zeeshan Ahmed; Saeed Amizadeh; Mikhail Bilenko; Rogan Carr; Wei-Sheng Chin; Yael Dekel; Xavier Dupré; Vadim Eksarevskiy; Senja Filipi; Tom Finley; Abhishek Goswami; Monte Hoover; et al. (KDD, 2019)

Machine Learning at Microsoft with ML .NET. - Zeeshan Ahmed; Saeed Amizadeh; Mikhail Bilenko; Rogan Carr; Wei-Sheng Chin; Yael Dekel; Xavier Dupré; Vadim Eksarevskiy; Eric Erhardt; Costin Eseanu; Senja Filipi; Tom Finley; et al. (CoRR, 2019)

MS-nowcasting: Operational Precipitation Nowcasting with Convolutional LSTMs at Microsoft Weather. - Sylwester Klocek; Haiyu Dong; Matthew Dixon; Panashe Kanengoni; Najeeb Kazmi; Pete Luferenko; Zhongjian Lv; Shikhar Sharma; Jonathan A. Weyn; Siqi Xiang (CoRR, 2021)

Super-resolution Probabilistic Rain Prediction from Satellite Data Using 3D U-Nets and EarthFormers. - Yang Li; Haiyu Dong; Zuliang Fang; Jonathan A. Weyn; Pete Luferenko (CoRR, 2022)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

An ensemble of data-driven weather prediction models for operational sub-seasonal forecasting. - Jonathan A. Weyn; Divya Kumar; Jeremy Berman; Najeeb Kazmi; Sylwester Klocek; Pete Luferenko; Kit Thambiratnam (CoRR, 2024)