activity
20192021
most citedTopological Data Analysis of Time Series Data for B2B Customer Relationship Management

9 citations · 24 across the 7 of their papers we have counts for

collaborators

11 papers

cs.LG2021

Adversarial Attacks on Deep Models for Financial Transaction Records

Ivan Fursov, Matvey Morozov, Nina Kaploukhaya +7

Machine learning models using transaction records as inputs are popular among financial institutions. The most efficient models use deep-learning architectures similar to those in…

cs.LG2021

COHORTNEY: Non-Parametric Clustering of Event Sequences

Vladislav Zhuzhel, Rodrigo Rivera-Castro, Nina Kaploukhaya +3

Cohort analysis is a pervasive activity in web analytics. One divides users into groups according to specific criteria and tracks their behavior over time. Despite its extensive us…

cs.LG2020

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…

cs.LG20203 cited

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…

stat.AP2020

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…

q-fin.PM20204 cited

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…