Stochastic variational inference algorithms are derived for fitting vari...
Emerging tools bring forth fresh approaches to work, and the field of na...
Antimicrobial resistance is becoming a major threat to public health
thr...
The amount of data has growing significance in exploring cutting-edge
ma...
This work examines how the dependence structures between energy futures ...
Clustering is an important task in many areas of knowledge: medicine and...
Dirichlet processes and their extensions have reached a great popularity...
Many approximate Bayesian inference methods assume a particular parametr...
Modelling and understanding directional gene networks is a major challen...
Copula models are flexible tools to represent complex structures of
depe...
This paper provides a review of Approximate Bayesian Computation (ABC)
m...
Improved communication systems, shrinking battery sizes and the price dr...
We propose a prior distribution for the number of components of a finite...
This chapter will appear in the forthcoming Handbook of Approximate Baye...
The Wallenius distribution is a generalisation of the Hypergeometric
dis...