Social distancing measures to reduce the spread of the novel coronavirus are in place worldwide. These guideline are for everyone. We are all expected to reduce our contact with others, and this will have some negative impacts in terms of mental health and loneliness, particularly for the elderly and other vulnerable groups. So why should we follow measures that seem so extreme? The answer is simple. Social distancing works. It reduces transmission of the virus effectively and lessens the impact on already stretched healthcare services.

Deep learning generalizes because the parameter-function map is biased towards simple functions
Pérez, G Louis, A Camargo, C 7th International Conference on Learning Representations, ICLR 2019 (01 Jan 2019)
Boolean Threshold Networks as Models of Genotype-Phenotype Maps
Camargo, C Louis, A Springer Proceedings in Complexity 143-155 (22 Feb 2020)
On monotonic determinacy and rewritability for recursive queries and views
Benedikt, M Kikot, S Ostropolski-Nalewaja, P Romero, M PODS'20: Proceedings of the 39th ACM SIGMOD-SIGACT-SIGAI Symposium on Principles of Database Systems 131-148 (14 Jun 2020)
ARCH-COMP19 Category Report: Stochastic Modelling
Abate, A Blom, H Cauchi, N Degiorgio, K Fränzle, M Moritz Hahn, E Haesaert, S Ma, H Oishi, M Pilch, C Remke, A Salamati, M Soudjani, S van Huijgevoort, B Vinod, A EPiC series in computing volume 61 62-20 (25 May 2019)
ARCH-COMP19 category report: hybrid systems with piecewise constant dynamics
Frehse, G Abate, A Adzkiya, D Becchi, A Bu, L Cimatti, A Giacobbe, M Griggio, A Mover, S Syifa'ul Mufid, M Riouak, I Tonetta, S Zaffanella, E 1-13 (25 May 2019)
Generic predictions of output probability based on complexities of inputs and outputs
Dingle, K Pérez, G Louis, A Scientific reports volume 10 issue 1 (10 Mar 2020)
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