A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
With the present revival of interest in bistatic radar systems, research in that area has gained momentum. Given some of the strategic advantages for a bistatic configuration, and tech- nological advances in the past few years, large-scale implementation of the bistatic systems is a scope for the near future. If the bi…
Achilles Tendon Rupture (ATR) is one of the typical soft tissue injuries. Rehabilitation after such a musculoskeletal injury remains a prolonged process with a very variable outcome. Accurately predicting rehabilitation outcome is crucial for treatment decision support. However, it is challenging to train an automatic …
Proposes a new method to improve target annotation in ATR.
Paper uses Bayesian optimization to find best Supertrend indicator settings.
Deployment and operation of autonomous underwater vehicles is expensive and time-consuming. High-quality realistic sonar data simulation could be of benefit to multiple applications, including training of human operators for post-mission analysis, as well as tuning and validation of autonomous target recognition (ATR) …
Forecast-to-fill strategy generates durable alpha in gold futures.
New method uses asymmetric Tsallis relative entropy for better risk assessment in financial portfolios.
FutureQuant Transformer predicts price ranges and volatility for futures trading.
Bayesian fusion improves radar target recognition for UAVs.
Quantum algorithms improve stock price prediction accuracy.
Statistical learning is the process of estimating an unknown probabilistic input-output relationship of a system using a limited number of observations. A statistical learning machine (SLM) is the algorithm, function, model, or rule, that learns such a process; and machine learning (ML) is the conventional name of this…