Even good bots fight: The case of Wikipedia http://dx.doi.org/10.1371/journal.pone.0171774 In recent years, there has been a huge increase in the number of...
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning International Joint Conference on Artificial Intelligence (IJCAI), 2017. Autonomous vehicle (AV) software is typically...
Conditions beyond treewidth for tightness of higher-order LP relaxations In Artificial Intelligence and Statistics (AISTATS), 2017. Poster will also be presented by Aldo...
Challenges for Transparency Workshop on Human Interpretability in Machine Learning (WHI) at ICML, August 2017. [best paper...
At the Crossroads: Lessons and Challenges in Computational Social Science Lausanne: Frontiers Media, doi: 10.3389/978-2-88945-021-3. We are nowadays at a social science crossroads, at...
Bayesian survival modelling of university outcomes DOI: 10.1111/rssa.12211 Dropouts and delayed graduations are critical issues in higher education systems world...
Beyond privacy and exposure: ethical issues within citizen-facing analytics Philosophical Translations of the Royal Society, volume 374, issue 2083. We discuss the governing...
Chainspace: A Sharded Smart Contracts Platform arXiv:1708.03778 Chainspace is a decentralized infrastructure, known as a distributed ledger, that supports user...
Bayesian Probabilistic Numerical Methods The emergent field of probabilistic numerics has thus far lacked clear statistical principals. This... Cockayne J, Oates CJ, Sullivan T, Girolami M. Bayesian Probabilistic Numerical Methods.
Bayesian Probabilistic Numerical Methods for Industrial Process Monitoring. The use of high-power industrial equipment, such as large-scale mixing equipment or a hydrocyclone... Oates CJ, Cockayne J, Aykroyd RG. Bayesian Probabilistic Numerical Methods for Industrial Process Monitoring.
Bayesian Quadrature for Multiple Related Integrals arXiv:1801.04153v2 Bayesian probabilistic numerical methods are a set of tools providing posterior distributions on...
Analysis of free text in electronic health records for identification of cancer patient trajectories doi:10.1038/srep46226 With an aging patient population and increasing complexity in patient disease trajectories, physicians...
A Bayesian Conjugate Gradient Method A fundamental task in numerical computation is the solution of large linear systems. The... Cockayne J, Oates CJ, Girolami M. A Bayesian Conjugate Gradient Method.
An Informational Right to the City? Code, Content, Control, and the Urbanization of Information DOI: 10.1111/anti.12312 Henri Lefebvre talked of the “right to the city” alongside a right...
Algorithms for Learning Sparse Additive Models with Interactions in High Dimensions arXiv:1605.00609 A function f:Rd→R is a Sparse Additive Model (SPAM), if it is of...
Aging increases cell-to-cell transcriptional variability upon immune stimulation DOI: 10.1126/science.aah4115 Aging is characterized by progressive loss of physiological and cellular functions, but...
A robust parallel algorithm for combinatorial compressed sensing In previous work two of the authors have shown that a vector x∈Rn with... Rodrigo Mendoza-Smith, Jared Tanner, and Florian Wechsung, “A robust parallel algorithm for combinatorial compressed sensing”, IEEE Transactions on Signal Processing, Vol. 66(8) (2018) 2167-2177.
A determinant-free method to simulate theparameters of large Gaussian fields DOI: 10.1002/sta4.153 We propose a determinant-free approach for simulation-based Bayesian inference in high-dimensional Gaussian...