DeXposure-Claw combines a graph time-series foundation model for forecasting DeFi networks with rule-based monitors and data-health gates to emit regulator-aligned risk tickets, evaluated via a new six-axis benchmark on five years of real weekly data.
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Temporal graph models on pseudotime-resolved gene regulatory networks from single-cell transcriptomics outperform static foundation models like scGPT on gene-expression forecasting, link prediction, and centrality tasks in two mouse developmental datasets.
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DeXposure-Claw: An Agentic System for DeFi Risk Supervision
DeXposure-Claw combines a graph time-series foundation model for forecasting DeFi networks with rule-based monitors and data-health gates to emit regulator-aligned risk tickets, evaluated via a new six-axis benchmark on five years of real weekly data.
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Applications of temporal graph learning for predicting the dynamics of biological systems
Temporal graph models on pseudotime-resolved gene regulatory networks from single-cell transcriptomics outperform static foundation models like scGPT on gene-expression forecasting, link prediction, and centrality tasks in two mouse developmental datasets.