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The subtle simplicity of cosmological correlators (2025)
Journal Article
Chowdhury, C., Lipstein, A., Mei, J., Sachs, I., & Vanhove, P. (in press). The subtle simplicity of cosmological correlators. Journal of High Energy Physics, 2025(3), Article 7. https://doi.org/10.1007/jhep03%282025%29007

We investigate cosmological correlators for conformally coupled ϕ4 theory in four-dimensional de Sitter space. These in-in correlators differ from scattering amplitudes for massless particles in flat space due to the spacelike structure of future inf... Read More about The subtle simplicity of cosmological correlators.

Winding and magnetic helicity in periodic domains (2025)
Journal Article
Xiao, D., Prior, C. B., & Yeates, A. R. (2025). Winding and magnetic helicity in periodic domains. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 481(2307), Article 20240152. https://doi.org/10.1098/rspa.2024.0152

In simply-connected Euclidean domains, it is well-known that the topological complexity of a given magnetic field can be quantified by its magnetic helicity, which is equivalent to the total, flux-weighted winding number of magnetic field lines. Ofte... Read More about Winding and magnetic helicity in periodic domains.

Bayesian classification of OXPHOS deficient skeletal myofibres (2025)
Journal Article
Childs, J., Golightly, A., Gomes, T. B., Vincent, A. E., & Lawless, C. (2025). Bayesian classification of OXPHOS deficient skeletal myofibres. PLoS Computational Biology, 21(2), Article e1012770. https://doi.org/10.1371/journal.pcbi.1012770

Mitochondria are organelles in most human cells which release the energy required for cells to function. Oxidative phosphorylation (OXPHOS) is a key biochemical process within mitochondria required for energy production and requires a range of protei... Read More about Bayesian classification of OXPHOS deficient skeletal myofibres.

Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient (2025)
Presentation / Conference Contribution
Dinh, V., Ho, L., & Nguyen, C. (2024, December). Hamiltonian Monte Carlo on ReLU Neural Networks is Inefficient. Presented at The Thirty-Eighth Annual Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada

A two-level multivariate response model for data with latent structures (2025)
Journal Article
Zhang, Y., Einbeck, J., & Drikvandi, R. (online). A two-level multivariate response model for data with latent structures. Statistical Modelling, https://doi.org/10.1177/1471082X241313024

A novel approach is proposed for analysing multilevel multivariate response data. The approach is based on identifying a one-dimensional latent variable spanning the space of responses, which then induces correlation between upper-level units. The la... Read More about A two-level multivariate response model for data with latent structures.

A short proof of Helson's conjecture (2025)
Journal Article
Gorodetsky, O., & Wong, M. D. (online). A short proof of Helson's conjecture. Bulletin of the London Mathematical Society, https://doi.org/10.1112/blms.70015

Let α : N → S 1 $\alpha \colon \mathbb {N}\rightarrow S^1$ be the Steinhaus multiplicative function: a completely multiplicative function such that ( α ( p ) ) p prime $(\alpha (p))_{p\text{ prime}}$ are i.i.d. random variables uniformly distributed... Read More about A short proof of Helson's conjecture.