9 citations · 22 across the 5 of their papers we have counts for
6 papers
Assessing the Risk of Permafrost Degradation with Physics-Informed Machine Learning
Polina Pilyugina, Timofey Chernikov, Alexey Zaytsev +6
Global warming accelerates permafrost degradation, impacting the reliability of critical infrastructure used by more than five million people daily. Furthermore, permafrost thaw pr…
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…
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…
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…
Topological Data Analysis of Time Series Data for B2B Customer Relationship Management
Rodrigo Rivera-Castro, Polina Pilyugina, Alexander Pletnev +3
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 to the…