physics-informed neural networks for lévy-driven pides. rigorous convergence analysis of numerical schemes for stochastic processes.

efficient ml via kernel optimisation. using numerical methods to determine how and why systems are fast, not just empirical findings.

high-performance c++20 rl kernels library. efficient implementations with mathematical complexity backing and pybind11 bindings.