Flow Matching for Credit Card Fraud Detection
Evaluate one-step flow matching for credit card fraud detection, comparing classification quality, training cost and inference speed with gradient boosted trees.
Large language models and news sentiment for algorithmic trading
This project investigates whether financial news sentiment extracted by large language models can improve trading signals, with an emphasis on Apple stock, news timing and rigorous backtesting.
Microbiome analysis, knowledge graphs and causality
Combining literature-derived knowledge graphs with microbiome observations to investigate causal hypotheses in personalized health.
Uncertainty quantification for large language models
This MMF project studies uncertainty estimates for transformer models, initially on tabular classification, with potential applications to the reliability of trading predictions.