Bohlke-Schneider, Michael

10 publications

AISTATS 2025 ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables Sebastian Pineda Arango, Pedro Mercado, Shubham Kapoor, Abdul Fatir Ansari, Lorenzo Stella, Huibin Shen, Hugo Henri Joseph Senetaire, Ali Caner Turkmen, Oleksandr Shchur, Danielle C. Maddix, Michael Bohlke-Schneider, Bernie Wang, Syama Sundar Rangapuram

AutoML 2025 Multi-Layer Stack Ensembles for Time Series Forecasting Nathanael Bosch, Oleksandr Shchur, Nick Erickson, Michael Bohlke-Schneider, Ali Caner Turkmen

TMLR 2024 Chronos: Learning the Language of Time Series Abdul Fatir Ansari, Lorenzo Stella, Ali Caner Turkmen, Xiyuan Zhang, Pedro Mercado, Huibin Shen, Oleksandr Shchur, Syama Sundar Rangapuram, Sebastian Pineda Arango, Shubham Kapoor, Jasper Zschiegner, Danielle C. Maddix, Hao Wang, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Bernie Wang

AISTATS 2023 Coherent Probabilistic Forecasting of Temporal Hierarchies Syama Sundar Rangapuram, Shubham Kapoor, Rajbir Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider

NeurIPS 2023 Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting Marcel Kollovieh, Abdul Fatir Ansari, Michael Bohlke-Schneider, Jasper Zschiegner, Hao Wang, Yuyang Wang

NeurIPSW 2022 Adaptive Sampling for Probabilistic Forecasting Under Distribution Shift Luca Masserano, Syama Sundar Rangapuram, Shubham Kapoor, Rajbir Singh Nirwan, Youngsuk Park, Michael Bohlke-Schneider

ICLR 2022 PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series Paul Jeha, Michael Bohlke-Schneider, Pedro Mercado, Shubham Kapoor, Rajbir Singh Nirwan, Valentin Flunkert, Jan Gasthaus, Tim Januschowski

MLOSS 2020 GluonTS: Probabilistic and Neural Time Series Modeling in Python Alexander Alexandrov, Konstantinos Benidis, Michael Bohlke-Schneider, Valentin Flunkert, Jan Gasthaus, Tim Januschowski, Danielle C. Maddix, Syama Rangapuram, David Salinas, Jasper Schulz, Lorenzo Stella, Ali Caner Türkmen, Yuyang Wang

NeurIPS 2020 Normalizing Kalman Filters for Multivariate Time Series Analysis Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski

NeurIPS 2019 High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes David Salinas, Michael Bohlke-Schneider, Laurent Callot, Roberto Medico, Jan Gasthaus