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Rangapuram, Syama Sundar
17  Ergebnisse:
Personensuche X
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1

Deep Learning for Time Series Forecasting: Tutorial and Lit..:

Benidis, Konstantinos ; Rangapuram, Syama Sundar ; Flunkert, Valentin...
ACM Computing Surveys.  55 (2022)  6 - p. 1-36 , 2022
Link: https://doi.org/10.1145/..
 
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2

METHODS FOR SPARSE AND LOW-RANK RECOVERY UNDER SIMPLEX CONS..:

Li, Ping ; Rangapuram, Syama Sundar ; Slawski, Martin
Statistica Sinica.  30 (2020)  2 - p. 557-577 , 2020
Link: https://www.jstor.org/st..
 
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3

Graph-based methods for unsupervised and semi-supervised da..:

Rangapuram, Syama Sundar , March 2016
Link: http://nbn-resolving.de/..
 
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4

Towards realistic team formation in social networks based o..:

, In: Proceedings of the 22nd international conference on World Wide Web,
Rangapuram, Syama Sundar ; Bühler, Thomas ; Hein, Matthias - p. 1077-1088 , 2013
Link: https://dl.acm.org/doi/1..
 
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5

Adaptive Sampling for Probabilistic Forecasting under Distr..:

Masserano, Luca ; Rangapuram, Syama Sundar ; Kapoor, Shubham...
http://arxiv.org/abs/2302.11870.  , 2023
Link: http://arxiv.org/abs/230..
 
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6

Deep Non-Parametric Time Series Forecaster:

Rangapuram, Syama Sundar ; Gasthaus, Jan ; Stella, Lorenzo...
http://arxiv.org/abs/2312.14657.  , 2023
Link: http://arxiv.org/abs/231..
 
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7

Multivariate Time Series Forecasting with Latent Graph Infe..:

Satorras, Victor Garcia ; Rangapuram, Syama Sundar ; Januschowski, Tim
http://arxiv.org/abs/2203.03423.  , 2022
Link: http://arxiv.org/abs/220..
 
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8

Neural Flows: Efficient Alternative to Neural ODEs:

Biloš, Marin ; Sommer, Johanna ; Rangapuram, Syama Sundar..
http://arxiv.org/abs/2110.13040.  , 2021
Link: http://arxiv.org/abs/211..
 
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9

Deep Learning for Time Series Forecasting: Tutorial and Lit..:

Benidis, Konstantinos ; Rangapuram, Syama Sundar ; Flunkert, Valentin...
http://arxiv.org/abs/2004.10240.  , 2020
Link: http://arxiv.org/abs/200..
 
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10

Methods for Sparse and Low-Rank Recovery under Simplex Cons..:

Li, Ping ; Rangapuram, Syama Sundar ; Slawski, Martin
http://arxiv.org/abs/1605.00507.  , 2016
Link: http://arxiv.org/abs/160..
 
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11

Graph-based methods for unsupervised and semi-supervised da..:

Rangapuram, Syama Sundar
http://nbn-resolving.org/urn:nbn:de:bsz:291-scidok-66590.  , 2016
Link: http://nbn-resolving.org..
 
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12

Constrained 1-Spectral Clustering:

Rangapuram, Syama Sundar ; Hein, Matthias
http://arxiv.org/abs/1505.06485.  , 2015
Link: http://arxiv.org/abs/150..
 
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13

Tight Continuous Relaxation of the Balanced $k$-Cut Problem:

Rangapuram, Syama Sundar ; Mudrakarta, Pramod Kaushik ; Hein, Matthias
http://arxiv.org/abs/1505.06478.  , 2015
Link: http://arxiv.org/abs/150..
 
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14

Towards Realistic Team Formation in Social Networks based o..:

Rangapuram, Syama Sundar ; Bühler, Thomas ; Hein, Matthias
http://arxiv.org/abs/1505.06661.  , 2015
Link: http://arxiv.org/abs/150..
 
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15

The Total Variation on Hypergraphs - Learning on Hypergraph..:

Hein, Matthias ; Setzer, Simon ; Jost, Leonardo.
http://arxiv.org/abs/1312.5179.  , 2013
Link: http://arxiv.org/abs/131..
 
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