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Publications

Naik, C. et al. (2023) “Bayesian Nonparametrics for Sparse Dynamic Networks”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Nature, pp. 191–206.
Naik, C. et al. (2023) “Bayesian Nonparametrics for Sparse Dynamic Networks”, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Springer Nature, pp. 191–206.
Saar, K. et al. (2023) “Turning high-throughput structural biology into predictive inhibitor design”, Proceedings of the National Academy of Sciences, 120(11).
Johnson, E., Pike-Burke, C. and Rebeschini, P. (2023) “Optimal Convergence Rate for Exact Policy Mirror Descent in Discounted Markov Decision Processes”, arXiv.
Lu, Y., Reinert, G. and Cucuringu, M. (2023) “Co-Trading Networks for Modeling Dynamic Interdependency Structures and Estimating High-Dimensional Covariances in US Equity Markets”, SSRN Electronic Journal.
Lu, Y., Reinert, G. and Cucuringu, M. (2023) “Co-trading networks for modeling dynamic interdependency structures and estimating high-dimensional covariances in US equity markets”, arXiv.
Caron, F. et al. (2023) “Over-parameterised Shallow Neural Networks with Asymmetrical Node Scaling: Global Convergence Guarantees and Feature Learning”, arXiv.
Dablander, M. et al. (2023) “Exploring QSAR models for activity-cliff prediction.”
Alfano, C., Yuan, R. and Rebeschini, P. (2023) “A Novel Framework for Policy Mirror Descent with General Parameterization and Linear Convergence”, arXiv.
Li, G. et al. (2023) “A spatio-temporal framework for modelling wastewater concentration during the COVID-19 pandemic”, Environment International, 172, pp. 107765–107765.