9 citations · 27 across the 11 of their papers we have counts for
7 papers · 1 filter
TOTOPO: Classifying univariate and multivariate time series with Topological Data Analysis
Polina Pilyugina, Rodrigo Rivera-Castro, Eugeny Burnaev
This work is devoted to a comprehensive analysis of topological data analysis fortime series classification. Previous works have significant shortcomings, such aslack of large-scal…
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting
Rodrigo Rivera-Castro, Aleksandr Pletnev, Polina Pilyugina +4
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure. Its use for time series data has been limited. In thi…
Graph Neural Networks for Model Recommendation using Time Series Data
Aleksandr Pletnev, Rodrigo Rivera-Castro, Evgeny Burnaev
Time series prediction aims to predict future values to help stakeholders make proper strategic decisions. This problem is relevant in all industries and areas, ranging from financ…
Topological Data Analysis for Portfolio Management of Cryptocurrencies
Rodrigo Rivera-Castro, Polina Pilyugina, Evgeny Burnaev
Portfolio management is essential for any investment decision. Yet, traditional methods in the literature are ill-suited for the characteristics and dynamics of cryptocurrencies. T…
An industry case of large-scale demand forecasting of hierarchical components
Rodrigo Rivera-Castro, Ivan Nazarov, Yuke Xiang +3
Demand forecasting of hierarchical components is essential in manufacturing. However, its discussion in the machine-learning literature has been limited, and judgemental forecasts…
Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks
Ivan Maksimov, Rodrigo Rivera-Castro, Evgeny Burnaev
Recommender systems have become an essential instrument in a wide range of industries to personalize the user experience. A significant issue that has captured both researchers' an…
DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data
Aiusha Sangadiev, Rodrigo Rivera-Castro, Kirill Stepanov +5
This work proposes DeepFolio, a new model for deep portfolio management based on data from limit order books (LOB). DeepFolio solves problems found in the state-of-the-art for LOB…