Syama Sundar Rangapuram

ORCID

Publication Activity (10 Years)

Years Active: 2012-2024
Publications (10 Years): 19

Top Venues

Saarland University, Saarbrücken, Germany (PHD)

Education History

Saarland University, Saarbrücken, Germany

PHD

Publications

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, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang
Chronos: Learning the Language of Time Series. CoRR (2024)
Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski
Deep Non-Parametric Time Series Forecaster. CoRR (2023)
Syama Sundar Rangapuram, Shubham Kapoor, Rajbir-Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider
Coherent Probabilistic Forecasting of Temporal Hierarchies. AISTATS (2023)
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) (2023)
Luca Masserano, Syama Sundar Rangapuram, Shubham Kapoor, Rajbir-Singh Nirwan, Youngsuk Park, Michael Bohlke-Schneider
Adaptive Sampling for Probabilistic Forecasting under Distribution Shift. CoRR (2023)
Victor Garcia Satorras, Syama Sundar Rangapuram, Tim Januschowski
Multivariate Time Series Forecasting with Latent Graph Inference. CoRR (2022)
Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann
Neural Flows: Efficient Alternative to Neural ODEs. NeurIPS (2021)
Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann
Neural Flows: Efficient Alternative to Neural ODEs. CoRR (2021)
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)
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)
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 (2020)
Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus
Deep Rao-Blackwellised Particle Filters for Time Series Forecasting. NeurIPS (2020)
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 (2020)
Edo Liberty, Zohar S. Karnin, Bing Xiang, Laurence Rouesnel, Baris Coskun, Ramesh Nallapati, Julio Delgado, Amir Sadoughi, Yury Astashonok, Piali Das, Can Balioglu, Saswata Chakravarty, Madhav Jha, Philip Gautier, David Arpin, Tim Januschowski, Valentin Flunkert, Yuyang Wang, Jan Gasthaus, Lorenzo Stella, Syama Sundar Rangapuram, David Salinas, Sebastian Schelter, Alex Smola
Elastic Machine Learning Algorithms in Amazon SageMaker. SIGMOD Conference (2020)
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 (2019)
Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski
Probabilistic Forecasting with Spline Quantile Function RNNs. AISTATS (2019)
Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski
Deep State Space Models for Time Series Forecasting. NeurIPS (2018)
Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert
Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale. CoRR (2017)
Ping Li, Syama Sundar Rangapuram, Martin Slawski
Methods for Sparse and Low-Rank Recovery under Simplex Constraints. CoRR (2016)
Syama Sundar Rangapuram, Matthias Hein
Constrained 1-Spectral Clustering. CoRR (2015)
Syama Sundar Rangapuram, Thomas Bühler, Matthias Hein
Towards Realistic Team Formation in Social Networks based on Densest Subgraphs. CoRR (2015)
Syama Sundar Rangapuram, Pramod Kaushik Mudrakarta, Matthias Hein
Tight Continuous Relaxation of the Balanced k-Cut Problem. CoRR (2015)
Syama Sundar Rangapuram, Pramod Kaushik Mudrakarta, Matthias Hein
Tight Continuous Relaxation of the Balanced k-Cut Problem. NIPS (2014)
Syama Sundar Rangapuram, Thomas Bühler, Matthias Hein
Towards realistic team formation in social networks based on densest subgraphs. WWW (2013)
Matthias Hein, Simon Setzer, Leonardo Jost, Syama Sundar Rangapuram
The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited. NIPS (2013)
Matthias Hein, Simon Setzer, Leonardo Jost, Syama Sundar Rangapuram
The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited. CoRR (2013)
Thomas Bühler, Syama Sundar Rangapuram, Simon Setzer, Matthias Hein
Constrained fractional set programs and their application in local clustering and community detection. ICML (1) (2013)
Thomas Bühler, Syama Sundar Rangapuram, Simon Setzer, Matthias Hein
Constrained fractional set programs and their application in local clustering and community detection. CoRR (2013)
Syama Sundar Rangapuram, Matthias Hein
Constrained 1-Spectral Clustering. AISTATS (2012)

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Publication Activity (10 Years)

Top Topics

Top Venues

Syama Sundar Rangapuram