2 citations · 3 across the 4 of their papers we have counts for
3 papers · 1 filter
On stochastic mirror descent with interacting particles: convergence properties and variance reduction
Anastasia Borovykh, Nikolas Kantas, Panos Parpas +1
An open problem in optimization with noisy information is the computation of an exact minimizer that is independent of the amount of noise. A standard practice in stochastic approx…
Optimally weighted loss functions for solving PDEs with Neural Networks
Remco van der Meer, Cornelis Oosterlee, Anastasia Borovykh
Recent works have shown that deep neural networks can be employed to solve partial differential equations, giving rise to the framework of physics informed neural networks. We intr…
On Calibration Neural Networks for extracting implied information from American options
Shuaiqiang Liu, Álvaro Leitao, Anastasia Borovykh +1
Extracting implied information, like volatility and/or dividend, from observed option prices is a challenging task when dealing with American options, because of the computational…