A Compact and Efficient Neural Data Structure for Mutual Information Estimation in Large Timeseries

Author:

Farokhmanesh Fatemeh1ORCID,Neuhauser Christoph1ORCID,Westermann Rüdiger1ORCID

Affiliation:

1. Department of Computer Science, School of Computation, Information and Technology, Technical University of Munich, Germany

Funder

Subproject A7 of the Transregional Collaborative Research Center SFB/TRR 165 "Waves to Weather" (www.wavestoweather.de) funded by the German Research Foundation (DFG)

Publisher

ACM

Reference47 articles.

1. Ramoza Ahsan, Rodica Neamtu, Muzammil Bashir, Elke A Rundensteiner, and Gabor Sarkozy. 2020. Correlation-Based Analytics of Time Series Data. In 2020 IEEE International Conference on Big Data (Big Data). IEEE, 4482–4491.

2. Mohamed Ishmael Belghazi, Aristide Baratin, Sai Rajeshwar, Sherjil Ozair, Yoshua Bengio, Aaron Courville, and Devon Hjelm. 2018. Mutual Information Neural Estimation. In Proceedings of the 35th International Conference on Machine Learning(Proceedings of Machine Learning Research, Vol. 80), Jennifer Dy and Andreas Krause (Eds.). PMLR, 531–540.

3. Xingyu Cai, Tingyang Xu, Jinfeng Yi, Junzhou Huang, and Sanguthevar Rajasekaran. 2019. Dtwnet: a dynamic time warping network. Advances in neural information processing systems 32 (2019).

4. Rohan Chabra, Jan E Lenssen, Eddy Ilg, Tanner Schmidt, Julian Straub, Steven Lovegrove, and Richard Newcombe. 2020. Deep local shapes: Learning local sdf priors for detailed 3d reconstruction. In Computer Vision–ECCV 2020: 16th European Conference, Glasgow, UK, August 23–28, 2020, Proceedings, Part XXIX 16. Springer, 608–625.

5. Learning Implicit Fields for Generative Shape Modeling

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