We introduce a new memory architecture for navigation in previously unseen environments, inspired by landmark-based navigation in animals. The proposed semiparametric topological memory (SPTM) consists of a (non-parametric) graph with nodes corresponding to locations in the environment and a (parametric) deep network capable of retrieving nodes from the graph based on observations. The graph st...

background: in survival studies when the event times are dependent, performing of the analysis by using of methods based on independent assumption, leads to biased. in this paper, using copula function and considering the dependence structure between the event times, a parametric joint distribution has made fitting to the events, and the effective factors on each of these events would be determ...

How to include censored data in a statistical analysis is a recurrent issue in statistics. In multivariate extremes, the dependence structure of large observations can be characterized in terms of a non parametric angular measure, while marginal excesses above asymptotically large thresholds have a parametric distribution. In this work, a flexible semi-parametric Dirichlet mixture model for ang...

In regression problems with errors having an unknown density f , least squares or robust M -estimation is the usual alternative to maximum likelihood, with the loss of asymptotic efficiency as a consequence. The search for efficiency in the absence of knowledge of f (adaptive estimation) has motivated a large amount of work, see in particular (Stein, 1956; Stone, 1975; Bickel, 1982) and the rev...

Despite a well-established correlation between alcohol intake and various risk-taking sexual behaviors, the causality remains unknown. I model the effect of alcohol use on the likelihood of pregnancy among youth using a variety of estimation techniques. The preference is given to the semi-parametric model where the cumulative distribution of heterogeneity is approximated by a 4-point discrete d...

In the last decades, considerable attention has been paid to the collection of antimicrobial resistance data, with the aim of monitoring non-wild-type isolates. This monitoring is performed based on minimum inhibition concentration (MIC) values, which are collected through dilution experiments. We present a semi-parametric mixture model to estimate the entire MIC density on the continuous scale...

Although there are recent developments for the analysis of first and second-order characteristics point processes on networks, very few attempts in introducing models network data. Motivated by crime data Bucaramanga (Colombia), we propose a spatiotemporal Hawkes process model adapted to events living linear networks. We consider non-parametric modelling strategy, which follow estimation both b...