Get started
Author

Michael Bohlke‐Schneider

Observed names: Bohlke-Schneider, Michael, Michael Bohlke-Schneider, Michael, Bohlke-Schneider
OpenAlex ID: A5034900644
An integrated workflow for crosslinking mass spectrometry
2019 · Marta L. Mendes, Lutz Fischer, et al. · Molecular Systems Biology · 236
PDF
Criteria for classifying forecasting methods
2019 · Tim Januschowski, Jan Gasthaus, et al. · International Journal of Forecasting · 211
PDF
GluonTS: Probabilistic and Neural Time Series Modeling in Python
2020 · A. Alexandrov, Konstantinos Benidis, et al. · Journal of Machine Learning Research · 119
High-Dimensional Multivariate Forecasting with Low-Rank Gaussian Copula Processes
2019 · Salinas, David, Bohlke-Schneider, Michael, et al. · arXiv (Cornell University) · 105
PDF
Chronos: Learning the Language of Time Series
2024 · Ansari, Abdul Fatir, Stella, Lorenzo, et al. · arXiv (Cornell University) · 85
PDF
GluonTS: Probabilistic Time Series Models in Python
2019 · Alexandrov, Alexander, Benidis, Konstantinos, et al. · arXiv (Cornell University) · 75
PDF
In Situ Structural Restraints from Cross-Linking Mass Spectrometry in Human Mitochondria
2019 · Petra S. J. Ryl, Michael Bohlke-Schneider, et al. · Journal of Proteome Research · 73
Neural forecasting: Introduction and literature overview.
2020 · Konstantinos Benidis, Syama Sundar Rangapuram, et al. · arXiv (Cornell University) · 68
Normalizing Kalman Filters for Multivariate Time Series Analysis
2020 · Emmanuel de Bézenac, Syama Sundar Rangapuram, et al. · neural information processing systems · 63
Predict, Refine, Synthesize: Self-Guiding Diffusion Models for Probabilistic Time Series Forecasting
2023 · Marcel Kollovieh, Abdul Fatir Ansari, et al. · neural information processing systems · 38
PDF
PSA-GAN: Progressive Self Attention GANs for Synthetic Time Series
2021 · Paul, Jeha, Michael, Bohlke-Schneider, et al. · arXiv (Cornell University) · 14
PDF
Resilient Neural Forecasting Systems
2020 · Michael Bohlke-Schneider, Shubham Kapoor, et al. · 10
PDF
A foundation model for multivariate time series forecasting
2026 · Abdul Fatir Ansari, Oleksandr Shchur, et al. · Research Square · 1
PDF
Zero-Shot Time Series Forecasting with Covariates via In-Context Learning
2025 · Auer, Andreas, Parthipan, Raghul, et al. · arXiv (Cornell University) · 1
PDF
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift
2023 · Masserano, Luca, Rangapuram, Syama Sundar, et al. · arXiv (Cornell University) · 1
PDF
Intrinsic Anomaly Detection for Multi-Variate Time Series
2022 · Rabanser, Stephan, Januschowski, Tim, et al. · arXiv (Cornell University) · 1
PDF
Leveraging novel information sources for protein structure prediction
2016 · Bohlke-Schneider, Michael · DepositOnce · 1
PathFM: Fast Generative Forecasting of Multivariate Trajectories
2026 · Yao, Jiachen, Zhang, Xiyuan, et al. · arXiv (Cornell University)
PDF
TCSAlgBench: Benchmarking Automated Proving for Research-Level Theoretical Computer Science
2026 · Yang, Chutong, Zhang, Xiyuan, et al. · arXiv (Cornell University)
PDF
Mitra-v2 Technical Report
2026 · Tao, Yefan, Zhang, Xiyuan, et al. · arXiv (Cornell University)
PDF
Correct, Concise and Complete: Multi-stage Training For Adaptive Reasoning
2026 · Nathanaël Carraz Rakotonirina, Ren Pang, et al. · Findings of the Association for Computational Linguistics: ACL (Findings of ACL)
PDF
A Flexible Forecasting Stack
2024 · Tim Januschowski, Yuyang Wang, et al. · Proceedings of the VLDB Endowment
On the Classification of ML and Statistical Forecasting Methods: Comments and Alternatives
2019 · Tim Januschowski, Laurent Callot, et al.
Works count: 27
Citation count: 1,124
H-index: 12
I10-index: 13
Year
Topic
Type