Syama Sundar Rangapuram

According to our database, Syama Sundar Rangapuram authored at least 25 papers between 2012 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Flexible Forecasting Stack.

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

Proc. VLDB Endow., August, 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, Michael W. Mahoney, Kari Torkkola, Andrew Gordon Wilson, Michael Bohlke-Schneider, Yuyang Wang

CoRR, 2024

2023

Deep Learning for Time Series Forecasting: Tutorial and Literature Survey.

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

ACM Comput. Surv., 2023

Deep Non-Parametric Time Series Forecaster.

Syama Sundar Rangapuram, Jan Gasthaus, Lorenzo Stella, Valentin Flunkert, David Salinas, Yuyang Wang, Tim Januschowski

CoRR, 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

Coherent Probabilistic Forecasting of Temporal Hierarchies.

Syama Sundar Rangapuram, Shubham Kapoor, Rajbir-Singh Nirwan, Pedro Mercado, Tim Januschowski, Yuyang Wang, Michael Bohlke-Schneider

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Multivariate Time Series Forecasting with Latent Graph Inference.

Victor Garcia Satorras, Syama Sundar Rangapuram, Tim Januschowski

CoRR, 2022

2021

Neural Flows: Efficient Alternative to Neural ODEs.

Marin Bilos, Johanna Sommer, Syama Sundar Rangapuram, Tim Januschowski, Stephan Günnemann

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

End-to-End Learning of Coherent Probabilistic Forecasts for Hierarchical Time Series.

Syama Sundar Rangapuram, Lucien D. Werner, Konstantinos Benidis, Pedro Mercado, Jan Gasthaus, Tim Januschowski

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

GluonTS: Probabilistic and Neural Time Series Modeling in Python.

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

J. Mach. Learn. Res., 2020

Neural forecasting: Introduction and literature overview.

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

CoRR, 2020

Elastic Machine Learning Algorithms in Amazon SageMaker.

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

Proceedings of the 2020 International Conference on Management of Data, 2020

Deep Rao-Blackwellised Particle Filters for Time Series Forecasting.

Richard Kurle, Syama Sundar Rangapuram, Emmanuel de Bézenac, Stephan Günnemann, Jan Gasthaus

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

2019

GluonTS: Probabilistic Time Series Models in Python.

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

CoRR, 2019

Probabilistic Forecasting with Spline Quantile Function RNNs.

Jan Gasthaus, Konstantinos Benidis, Yuyang Wang, Syama Sundar Rangapuram, David Salinas, Valentin Flunkert, Tim Januschowski

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018

Deep State Space Models for Time Series Forecasting.

Syama Sundar Rangapuram, Matthias W. Seeger, Jan Gasthaus, Lorenzo Stella, Yuyang Wang, Tim Januschowski

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

Approximate Bayesian Inference in Linear State Space Models for Intermittent Demand Forecasting at Scale.

Matthias W. Seeger, Syama Sundar Rangapuram, Yuyang Wang, David Salinas, Jan Gasthaus, Tim Januschowski, Valentin Flunkert

CoRR, 2017

2016

Graph-based methods for unsupervised and semi-supervised data analysis.

Syama Sundar Rangapuram

PhD thesis, 2016

Methods for Sparse and Low-Rank Recovery under Simplex Constraints.

Ping Li, Syama Sundar Rangapuram, Martin Slawski

CoRR, 2016

2014

Tight Continuous Relaxation of the Balanced k-Cut Problem.

Syama Sundar Rangapuram, Pramod Kaushik Mudrakarta, Matthias Hein

Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014

2013

Towards realistic team formation in social networks based on densest subgraphs.

Syama Sundar Rangapuram, Thomas Bühler, Matthias Hein

Proceedings of the 22nd International World Wide Web Conference, 2013

The Total Variation on Hypergraphs - Learning on Hypergraphs Revisited.

Matthias Hein, Simon Setzer, Leonardo Jost, Syama Sundar Rangapuram

Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 5-8, 2013

Constrained fractional set programs and their application in local clustering and community detection.

Thomas Bühler, Syama Sundar Rangapuram, Simon Setzer, Matthias Hein

Proceedings of the 30th International Conference on Machine Learning, 2013

2012

Constrained 1-Spectral Clustering.

Syama Sundar Rangapuram, Matthias Hein

Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012