1 citations · 1 across the 3 of their papers we have counts for
3 papers
math.PR2025
Rate estimates for weighted total variation norm in terms of Wasserstein distances
Iván Ivkovic, Miklós Rásonyi
We study the weighted total variation distance between probability measures. Using Fourier-analytic tools, we present estimates in terms of Wasserstein distances between the respec…
cs.LG2024
Parameter Estimation of Long Memory Stochastic Processes with Deep Neural Networks
Bálint Csanády, Lóránt Nagy, Dániel Boros +5
We present a purely deep neural network-based approach for estimating long memory parameters of time series models that incorporate the phenomenon of long-range dependence. Paramet…
stat.ML2024★ 1 cited
Deep learning the Hurst parameter of linear fractional processes and assessing its reliability
Dániel Boros, Bálint Csanády, Iván Ivkovic +3
This research explores the reliability of deep learning, specifically Long Short-Term Memory (LSTM) networks, for estimating the Hurst parameter in fractional stochastic processes.…