Non-parametric online market regime detection and regime clustering for multidimensional and path-dependent data structures by Issa, Z, Horvath, B

“…</p> <p>On the same principles, we also present a path-wise method for regime clustering which extends our previous work. …”

Clustering market regimes using the Wasserstein distance by Horvath, B, Issa, Z, Muguruza, A

“…The problem of rapid and automated detection of distinct market regimes is a topic of great interest to financial mathematicians and practitioners alike. …”

Distribution regression for sequential data by Lemercier, M, Salvi, C, Damoulas, T, Bonilla, EV, Lyons, T

“…Each is suited to a different data regime in terms of the number of data streams and the dimensionality of the individual streams. …”

Age evolution in the mean field forest fire model via multitype branching processes by Crane, E, Rath, B, Yeo, D

“…We consider the asymptotic regime of lightning rates for which the model displays self-organized criticality. …”

Neural rough differential equations for long time series by Morrill, J, Salvi, C, Kidger, P, Foster, J, Lyons, T

“…This extension has a purpose: by generalising the Neural CDE approach to a broader class of driving signals, we demonstrate particular advantages for tackling long time series. In this regime, we demonstrate efficacy on problems of length up to 17k observations and observe significant training speed-ups, improvements in model performance, and reduced memory requirements compared to existing approaches.…”

Bringing COVID-19 home for Christmas: a need for enhanced testing in healthcare institutions after the holidays by Smith, DRM, Duval, A, Zahar, JR, Opatowski, L, Temime, L

“…We propose a two-stage post-holiday testing regime as a means to maximize case detection and mitigate the risk of nosocomial COVID-19 outbreaks into the start of the new year. …”

On RKHS choices for assessing graph generators via kernel Stein statistics by Weckbecker, M, Xu, W, Reinert, G

“…We investigate the power performance and the computational runtime of the test in different scenarios, including both dense and sparse graph regimes. Experimental results on kernel performance for model assessment tasks are shown and discussed on synthetic and real-world network applications.…”