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ORCIDKonstantinos Benidis
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2020 – today
- 2024
[j6]Tim Januschowski, Yuyang Wang, Jan Gasthaus, Syama Sundar Rangapuram, Caner Turkmen, Jasper Zschiegner, Lorenzo Stella, Michael Bohlke-Schneider, Danielle C. Maddix, Konstantinos Benidis, Alexander Alexandrov, Christos Faloutsos, Sebastian Schelter:
A Flexible Forecasting Stack. Proc. VLDB Endow. 17(12): 3883-3892 (2024)- 2023
- [j5]Konstantinos Benidis
, Syama Sundar Rangapuram, Valentin Flunkert, Yuyang Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, François-Xavier Aubet, Laurent Callot, Tim Januschowski:
Deep Learning for Time Series Forecasting: Tutorial and Literature Survey. ACM Comput. Surv. 55(6): 121:1-121:36 (2023) - [i7]Konstantinos Benidis, Ugo Rosolia, Syama Rangapuram, George Iosifidis, Georgios S. Paschos:
Solving Recurrent MIPs with Semi-supervised Graph Neural Networks. CoRR abs/2302.11992 (2023) - [i6]Konstantinos Benidis, Georgios S. Paschos, Martin Groß, George Iosifidis:
Middle-mile optimization for next-day delivery. CoRR abs/2310.18388 (2023) - 2022
- [c7]Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus:
Multivariate Quantile Function Forecaster. AISTATS 2022: 10603-10621 - [i5]Kelvin Kan, François-Xavier Aubet, Tim Januschowski, Youngsuk Park, Konstantinos Benidis, Lars Ruthotto, Jan Gasthaus:
Multivariate Quantile Function Forecaster. CoRR abs/2202.11316 (2022) - 2021
- [c6]Syama Sundar Rangapuram, Lucien D. Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski:
End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series. ICML 2021: 8832-8843 - [c5]Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Bernie Wang, Tim Januschowski:
Deep Explicit Duration Switching Models for Time Series. NeurIPS 2021: 29949-29961 - [i4]Abdul Fatir Ansari, Konstantinos Benidis, Richard Kurle, Ali Caner Türkmen, Harold Soh, Alexander J. Smola, Yuyang Wang, Tim Januschowski:
Deep Explicit Duration Switching Models for Time Series. CoRR abs/2110.13878 (2021) - 2020
- [j4]Alexander Alexandrov, 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, Yuyang Wang:
GluonTS: Probabilistic and Neural Time Series Modeling in Python. J. Mach. Learn. Res. 21: 116:1-116:6 (2020) - [c4]Emmanuel de Bézenac, Syama Sundar Rangapuram, Konstantinos Benidis, Michael Bohlke-Schneider, Richard Kurle, Lorenzo Stella, Hilaf Hasson, Patrick Gallinari, Tim Januschowski:
Normalizing Kalman Filters for Multivariate Time Series Analysis. NeurIPS 2020 - [i3]Konstantinos Benidis, Syama Sundar Rangapuram, Valentin Flunkert, Bernie Wang, Danielle C. Maddix, Ali Caner Türkmen, Jan Gasthaus, Michael Bohlke-Schneider, David Salinas, Lorenzo Stella, Laurent Callot, Tim Januschowski:
Neural forecasting: Introduction and literature overview. CoRR abs/2004.10240 (2020)
2010 – 2019
- 2019
- [c3]Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski:
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS 2019: 1901-1910 - [i2]Alexander Alexandrov, 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, Yuyang Wang:
GluonTS: Probabilistic Time Series Models in Python. CoRR abs/1906.05264 (2019) - 2018
- [j3]Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar:
Optimization Methods for Financial Index Tracking: From Theory to Practice. Found. Trends Optim. 3(3): 171-279 (2018) - [j2]Konstantinos Benidis, Yiyong Feng, Daniel P. Palomar:
Sparse Portfolios for High-Dimensional Financial Index Tracking. IEEE Trans. Signal Process. 66(1): 155-170 (2018) - 2016
- [j1]Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel P. Palomar:
Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation. IEEE Trans. Signal Process. 64(23): 6211-6226 (2016) - [c2]Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Orthogonal sparse eigenvectors: A procrustes problem. ICASSP 2016: 4683-4686 - [i1]Konstantinos Benidis, Ying Sun, Prabhu Babu, Daniel Pérez Palomar:
Orthogonal Sparse PCA and Covariance Estimation via Procrustes Reformulation. CoRR abs/1602.03992 (2016) - 2013
- [c1]Konstantinos Benidis, Rafael F. Schaefer, Holger Boche:
Bidirectional relay communication with additional private message. SPAWC 2013: 41-45
Coauthor Index
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