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Found 11 papers, 2 papers with code
Continuous-time convolutions model of event sequences
Massive samples of event sequences data occur in various domains, including e-commerce, healthcare, and finance.
Adversarial Attacks on Deep Models for Financial Transaction Records
In this work, we examine adversarial attacks on transaction records data and defences from these attacks.
COHORTNEY: Non-Parametric Clustering of Event Sequences
Cohort analysis is a pervasive activity in web analytics.
TOTOPO: Classifying univariate and multivariate time series with Topological Data Analysis
This work is devoted to a comprehensive analysis of topological data analysis fortime series classification.
Graph Neural Networks for Model Recommendation using Time Series Data
The results show the relevancy and suitability of GNN as methods for model recommendations in time series forecasting.
Applications
Topology-based Clusterwise Regression for User Segmentation and Demand Forecasting
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure.
Addressing Cold Start in Recommender Systems with Hierarchical Graph Neural Networks
Recommender systems have become an essential instrument in a wide range of industries to personalize the user experience.
Topological Data Analysis for Portfolio Management of Cryptocurrencies
Portfolio management is essential for any investment decision.
DeepFolio: Convolutional Neural Networks for Portfolios with Limit Order Book Data
Further, we use DeepFolio for optimal portfolio allocation of crypto-assets with rebalancing.
Topological Data Analysis of Time Series Data for B2B Customer Relationship Management
Topological Data Analysis (TDA) is a recent approach to analyze data sets from the perspective of their topological structure.
Demand forecasting techniques for build-to-order lean manufacturing supply chains
Due to their nature, they differ significantly from traditional supply chains.
