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Found 4 papers, 1 papers with code
Scrutinizing Shipment Records To Thwart Illegal Timber Trade
The task of finding such fraudulent activities using trade data, in the absence of ground truth, can be modelled as an unsupervised anomaly detection problem.
Lessons from Deep Learning applied to Scholarly Information Extraction: What Works, What Doesn't, and Future Directions
We demonstrate how EneRex is able to extract key insights and trends from a large-scale dataset in the domain of computer science.
Detecting Anomalies Through Contrast in Heterogeneous Data
Among other challenges annotations are unavailable for our large-scale trade data with heterogeneous features (categorical and continuous), that can assist in building automated systems to detect fraudulent transactions.
Hierarchical Quickest Change Detection via Surrogates
We propose hierarchical quickest change detection (HQCD), a framework that formalizes the process of incorporating additional correlated sources for early changepoint detection.
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