Leveraging novel information sources for protein structure prediction (Nutzung neuer Informationsquellen für die Proteinstrukturvorhersage) - Michael Bohlke-Schneider (2016)

High-dimensional multivariate forecasting with low-rank Gaussian Copula Processes. - David Salinas; Michael Bohlke-Schneider; Laurent Callot; Roberto Medico; Jan Gasthaus (NeurIPS, 2019)

GluonTS: Probabilistic Time Series Models in Python. - Alexander Alexandrov 001; Konstantinos Benidis; Michael Bohlke-Schneider; Valentin Flunkert; Jan Gasthaus; Tim Januschowski; Danielle C. Maddix; Syama Sundar Rangapuram; David Salinas; Jasper Schulz; Lorenzo Stella; Ali Caner Türkmen; et al. (CoRR, 2019)

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, 2020)

Resilient Neural Forecasting Systems. - Michael Bohlke-Schneider; Shubham Kapoor; Tim Januschowski (DEEM@SIGMOD, 2020)

Neural forecasting: Introduction and literature overview. - Konstantinos Benidis; Syama Sundar Rangapuram; Valentin Flunkert; Bernie Wang 001; Danielle C. Maddix; Ali Caner Türkmen; Jan Gasthaus; Michael Bohlke-Schneider; David Salinas; Lorenzo Stella; Laurent Callot; Tim Januschowski (CoRR, 2020)

GluonTS: Probabilistic and Neural Time Series Modeling in Python. - Alexander Alexandrov 001; Konstantinos Benidis; Michael Bohlke-Schneider; Valentin Flunkert; Jan Gasthaus; Tim Januschowski; Danielle C. Maddix; Syama Sundar Rangapuram; David Salinas; Jasper Schulz; Lorenzo Stella; Ali Caner Türkmen; et al. (J. Mach. Learn. Res., 2020)

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 (ICLR, 2022)

Intrinsic Anomaly Detection for Multi-Variate Time Series. - Stephan Rabanser; Tim Januschowski; Kashif Rasul; Oliver Borchert; Richard Kurle; Jan Gasthaus; Michael Bohlke-Schneider; Nicolas Papernot; Valentin Flunkert (CoRR, 2022)

Criteria for Classifying Forecasting Methods. - Tim Januschowski; Jan Gasthaus; Yuyang Wang 001; David Salinas; Valentin Flunkert; Michael Bohlke-Schneider; Laurent Callot (CoRR, 2022)

Coherent Probabilistic Forecasting of Temporal Hierarchies. - Syama Sundar Rangapuram; Shubham Kapoor; Rajbir-Singh Nirwan; Pedro Mercado; Tim Januschowski; Yuyang Wang 001; Michael Bohlke-Schneider (AISTATS, 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 014; Yuyang Wang 001 (NeurIPS, 2023)

Adaptive Sampling for Probabilistic Forecasting under Distribution Shift. - Luca Masserano; Syama Sundar Rangapuram; Shubham Kapoor; Rajbir-Singh Nirwan; Youngsuk Park; Michael Bohlke-Schneider (CoRR, 2023)

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. - Konstantinos Benidis; Syama Sundar Rangapuram; Valentin Flunkert; Yuyang Wang 001; Danielle C. Maddix; Ali Caner Türkmen; Jan Gasthaus; Michael Bohlke-Schneider; David Salinas; Lorenzo Stella; François-Xavier Aubet; Laurent Callot; et al. (ACM Comput. Surv., 2023)

Chronos: Learning the Language of Time Series. - Abdul Fatir Ansari; Lorenzo Stella; Ali Caner Türkmen; Xiyuan Zhang; Pedro Mercado; Huibin Shen; Oleksandr Shchur; Syama Sundar Rangapuram; Sebastian Pineda-Arango; Shubham Kapoor; Jasper Zschiegner; Danielle C. Maddix; et al. (CoRR, 2024)

Chronos: Learning the Language of Time Series. - Abdul Fatir Ansari; Lorenzo Stella; Ali Caner Türkmen; Xiyuan Zhang; Pedro Mercado; Huibin Shen; Oleksandr Shchur; Syama Sundar Rangapuram; Sebastian Pineda-Arango; Shubham Kapoor; Jasper Zschiegner; Danielle C. Maddix; et al. (Trans. Mach. Learn. Res., 2024)

A Flexible Forecasting Stack. - Tim Januschowski; Yuyang Wang 001; Jan Gasthaus; Syama Sundar Rangapuram; Caner Türkmen; Jasper Zschiegner; Lorenzo Stella; Michael Bohlke-Schneider; Danielle C. Maddix; Konstantinos Benidis; Alexander Alexandrov 001; Christos Faloutsos; et al. (Proc. VLDB Endow., 2024)

ChronosX: Adapting Pretrained Time Series Models with Exogenous Variables. - Sebastian Pineda Arango; Pedro Mercado; Shubham Kapoor; Abdul Fatir Ansari; Lorenzo Stella; Huibin Shen; Hugo Senetaire; Ali Caner Türkmen; Oleksandr Shchur; Danielle C. Maddix; Michael Bohlke-Schneider; Bernie Wang 001; et al. (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 Senetaire; Caner Turkmen; Oleksandr Shchur; Danielle C. Maddix; Michael Bohlke-Schneider; Yuyang Wang 001; et al. (CoRR, 2025)

Zero-Shot Time Series Forecasting with Covariates via In-Context Learning. - Andreas Auer; Raghul Parthipan; Pedro Mercado; Abdul Fatir Ansari; Lorenzo Stella; Yuyang Wang 001; Michael Bohlke-Schneider; Syama Sundar Rangapuram (CoRR, 2025)