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.
Gradient-enhanced deep GPs improve multifidelity model accuracy.
Gradient-enhanced GSA uses Poincaré chaos expansions for accurate sensitivity analysis.
Develops a gradient-enhanced approach for online estimation in high-dimensional generalized linear models with streaming data.
Surrogate models provide a low computational cost alternative to evaluating expensive functions. The construction of accurate surrogate models with large numbers of independent variables is currently prohibitive because it requires a large number of function evaluations. Gradient-enhanced kriging has the potential to r…
Efficient method for high-dimensional American option pricing and hedging.
Enhanced Gaussian process regression for multi-fidelity data fusion.
SGE-Kriging reduces high-dimensional surrogate modelling costs.
HTE improves PINNs for high-dimensional, high-order PDEs by reducing computational cost and memory usage.
An exciting branch of machine learning research focuses on methods for learning, optimizing, and integrating unknown functions that are difficult or costly to evaluate. A popular Bayesian approach to this problem uses a Gaussian process (GP) to construct a posterior distribution over the function of interest given a se…