High dimensional inference

Polygonal Unadjusted Langevin Algorithms: Creating stable and efficient adaptive algorithms for neural networks. Lim, D-Y. & Sabanis, S. 2021. arXiv:2105.13937 [cs.LG]

Bengio, Yoshua, Prateek Gupta, Tegan Maharaj, Nasim Rahaman, Martin Weiss, Tristan Deleu, Eilif Muller et al. "Predicting Infectiousness for Proactive Contact Tracing." ICLR 2020.

A fully data-driven approach to minimizing CVaR for portfolio of assets via SGLD with discontinuous updating. Sabanis, Sotirios; Zhang, Ying. arXiv:2007.01672 [q-fin.PM]

Taming neural networks with TUSLA : Non-convex learning via adaptive stochastic gradient Langevin algorithms. Lovas, Attila; Lytras, Iosif ; Rásonyi, Miklós ; Sabanis, Sotirios. arXiv:2006.14514 [cs.LG]

Nonasymptotic analysis of Stochastic Gradient Hamiltonian Monte Carlo under local conditions for nonconvex optimization. Akyildiz, Ömer Deniz ; Sabanis, Sotirios. arXiv:2002.05465 [math.OC]

Vallejos (2019), "Exploring a world of a thousand dimensions", Nature Biotechnology

Vallejos (2019), "Exploring a world of a thousand dimensions", Nature Biotechnology

Robert Lung, Yue Wu, Dimitris Kamilis, Nick Polydorides, “A Sketched Finite Element Method for Elliptic Models”, https://arxiv.org/abs/1907.09852

Märtens, K., Campbell, K. R., Yau, C. (2019) Proceedings of the 36th International Conference on Machine Learning, PMLR 97:4372-4381.