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Syama Sundar Rangapuram
Syama Sundar Rangapuram
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Title
Cited by
Cited by
Year
Deep state space models for time series forecasting
SS Rangapuram, MW Seeger, J Gasthaus, L Stella, Y Wang, ...
Advances in neural information processing systems 31, 2018
7392018
Gluonts: Probabilistic and neural time series modeling in python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
Journal of Machine Learning Research 21 (116), 1-6, 2020
2192020
Probabilistic forecasting with spline quantile function RNNs
J Gasthaus, K Benidis, Y Wang, SS Rangapuram, D Salinas, V Flunkert, ...
The 22nd international conference on artificial intelligence and statistics …, 2019
1712019
The total variation on hypergraphs-learning on hypergraphs revisited
M Hein, S Setzer, L Jost, SS Rangapuram
Advances in Neural Information Processing Systems 26, 2013
1612013
Elastic machine learning algorithms in amazon sagemaker
E Liberty, Z Karnin, B Xiang, L Rouesnel, B Coskun, R Nallapati, ...
Proceedings of the 2020 ACM SIGMOD International Conference on Management of …, 2020
1292020
Deep learning for time series forecasting: Tutorial and literature survey
K Benidis, SS Rangapuram, V Flunkert, Y Wang, D Maddix, C Turkmen, ...
ACM Computing Surveys 55 (6), 1-36, 2022
1282022
Neural forecasting: Introduction and literature overview
K Benidis, SS Rangapuram, V Flunkert, B Wang, D Maddix, C Turkmen, ...
arXiv preprint arXiv:2004.10240 6, 2020
1172020
Normalizing kalman filters for multivariate time series analysis
E de Bézenac, SS Rangapuram, K Benidis, M Bohlke-Schneider, R Kurle, ...
Advances in Neural Information Processing Systems 33, 2995-3007, 2020
1122020
Towards realistic team formation in social networks based on densest subgraphs
SS Rangapuram, T Bühler, M Hein
Proceedings of the 22nd international conference on World Wide Web, 1077-1088, 2013
1102013
Constrained 1-spectral clustering
SS Rangapuram, M Hein
Artificial Intelligence and Statistics, 1143-1151, 2012
1052012
Gluonts: Probabilistic time series models in python
A Alexandrov, K Benidis, M Bohlke-Schneider, V Flunkert, J Gasthaus, ...
arXiv preprint arXiv:1906.05264, 2019
1032019
End-to-end learning of coherent probabilistic forecasts for hierarchical time series
SS Rangapuram, LD Werner, K Benidis, P Mercado, J Gasthaus, ...
International Conference on Machine Learning, 8832-8843, 2021
702021
Neural flows: Efficient alternative to neural ODEs
M Biloš, J Sommer, SS Rangapuram, T Januschowski, S Günnemann
Advances in neural information processing systems 34, 21325-21337, 2021
532021
Deep rao-blackwellised particle filters for time series forecasting
R Kurle, SS Rangapuram, E de Bézenac, S Günnemann, J Gasthaus
Advances in Neural Information Processing Systems 33, 15371-15382, 2020
332020
Approximate Bayesian inference in linear state space models for intermittent demand forecasting at scale
M Seeger, S Rangapuram, Y Wang, D Salinas, J Gasthaus, ...
arXiv preprint arXiv:1709.07638, 2017
262017
Tight continuous relaxation of the balanced k-cut problem
SS Rangapuram, PK Mudrakarta, M Hein
Advances in Neural Information Processing Systems 27, 2014
262014
Multivariate time series forecasting with latent graph inference
VG Satorras, SS Rangapuram, T Januschowski
arXiv preprint arXiv:2203.03423, 2022
222022
Deep Learning for Forecasting: Current Trends and Challenges.
T Januschowski, J Gasthaus, Y Wang, SS Rangapuram, L Callot
Foresight: The International Journal of Applied Forecasting, 2018
222018
Artificial intelligence system combining state space models and neural networks for time series forecasting
S Rangapuram, JA Gasthaus, T Januschowski, M Seeger, L Stella
US Patent 11,281,969, 2022
212022
Constrained fractional set programs and their application in local clustering and community detection
T Bühler, SS Rangapuram, S Setzer, M Hein
International Conference on Machine Learning, 624-632, 2013
212013
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Articles 1–20