1 code implementation • 29 Nov 2021 • Oskar Triebe, Hansika Hewamalage, Polina Pilyugina, Nikolay Laptev, Christoph Bergmeir, Ram Rajagopal
NeuralProphet is a hybrid forecasting framework based on PyTorch and trained with standard deep learning methods, making it easy for developers to extend the framework.
no code implementations • NeurIPS Workshop TDA_and_Beyond 2020 • Polina Pilyugina, Rodrigo Rivera-Castro, Eugeny Burnaev
This work is devoted to a comprehensive analysis of topological data analysis fortime series classification.
no code implementations • 8 Sep 2020 • Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina, Grecia Diaz, Ivan Nazarov, Wanyi Zhu, Evgeny Burnaev
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure.
no code implementations • 7 Sep 2020 • Rodrigo Rivera-Castro, Polina Pilyugina, Evgeny Burnaev
Portfolio management is essential for any investment decision.
no code implementations • 27 Aug 2020 • Aiusha Sangadiev, Rodrigo Rivera-Castro, Kirill Stepanov, Andrey Poddubny, Kirill Bubenchikov, Nikita Bekezin, Polina Pilyugina, Evgeny Burnaev
Further, we use DeepFolio for optimal portfolio allocation of crypto-assets with rebalancing.
no code implementations • 26 May 2019 • Rodrigo Rivera-Castro, Polina Pilyugina, Alexander Pletnev, Ivan Maksimov, Wanyi Wyz, Evgeny Burnaev
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure.