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Navigating the Dynamics of Financial Embeddings over Time
Financial transactions constitute connections between entities and through these connections a large scale heterogeneous weighted graph is formulated.
Quantifying Challenges in the Application of Graph Representation Learning
Graph Representation Learning (GRL) has experienced significant progress as a means to extract structural information in a meaningful way for subsequent learning tasks.
On the Interpretability and Evaluation of Graph Representation Learning
With the rising interest in graph representation learning, a variety of approaches have been proposed to effectively capture a graph's properties.
DeepTrax: Embedding Graphs of Financial Transactions
In this paper, we present a novel application of representation learning to bipartite graphs of credit card transactions in order to learn embeddings of account and merchant entities.
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