GP-SUM. Gaussian Processes Filtering of non-Gaussian Beliefs

This work studies the problem of stochastic dynamic filtering and state propagation with complex beliefs. The main contribution is GP-SUM, a filtering algorithm tailored to dynamic systems and observation models expressed as Gaussian Processes (GP), and to states represented as a weighted sum of Gaussians. The key attribute of GP-SUM is that it does not rely on linearizations of the dynamic or observation models, or on unimodal Gaussian approximations of the belief, hence enables tracking complex state distributions. The algorithm can be seen as a combination of a sampling-based filter with a probabilistic Bayes filter. On the one hand, GP-SUM operates by sampling the state distribution and propagating each sample through the dynamic system and observation models. On the other hand, it achieves effective sampling and accurate probabilistic propagation by relying on the GP form of the system, and the sum-of-Gaussian form of the belief. We show that GP-SUM outperforms several GP-Bayes and Particle Filters on a standard benchmark. We also demonstrate its use in a pushing task, predicting with experimental accuracy the naturally occurring non-Gaussian distributions.Comment: WAFR 2018, 16 pages, 7 figure

Depression and anxiety in relation to catechol-O-methyltransferase Val158Met genotype in the general population: The Nord-Trøndelag Health Study (HUNT)

<p>Abstract</p> <p>Background</p> <p>The catechol-O-methyltransferase (COMT) gene contains a functional polymorphism, Val158Met, which has been linked to anxiety and depression, but previous results are not conclusive. The aim of the present study was to examine the relationship between the Val158Met COMT gene polymorphism and anxiety and depression measured by the Hospital Anxiety and Depression Scale (HADS) in the general adult population.</p> <p>Methods</p> <p>In the Nord-Trøndelag Health Study (HUNT) the association between the Val158Met polymorphism and anxiety and depression was evaluated in a random sample of 5531 individuals. Two different cut off scores (≥ 8 and ≥ 11) were used to identify cases with anxiety (HADS-A) and depression (HADS-D), whereas controls had HADS-A <8 and HADS-D <8.</p> <p>Results</p> <p>The COMT genotype distribution was similar between controls and individuals in the groups with anxiety and depression using cut-off scores of ≥ 8. When utilizing the alternative cut-off score HADS-D ≥ 11, Met/Met genotype and Met allele were less common among men with depression compared to the controls (genotype: p = 0.017, allele: p = 0.006). In the multivariate analysis, adjusting for age and heart disease, depression (HADS-D ≥ 11) was less likely among men with the Met/Met genotype than among men with the Val/Val genotype (OR = 0.37, 95% CI = 0.18–0.76).</p> <p>Conclusion</p> <p>In this population-based study, no clear association between the Val158Met polymorphism and depression and anxiety was revealed. The Met/Met genotype was less likely among men with depression defined as HADS-D ≥ 11, but this may be an incidental finding.</p

The course of mental health after miscarriage and induced abortion: a longitudinal, five-year follow-up study

BACKGROUND: Miscarriage and induced abortion are life events that can potentially cause mental distress. The objective of this study was to determine whether there are differences in the patterns of normalization of mental health scores after these two pregnancy termination events. METHODS: Forty women who experienced miscarriages and 80 women who underwent abortions at the main hospital of Buskerud County in Norway were interviewed. All subjects completed the following questionnaires 10 days (T1), six months (T2), two years (T3) and five years (T4) after the pregnancy termination: Impact of Event Scale (IES), Quality of Life, Hospital Anxiety and Depression Scale (HADS), and another addressing their feelings about the pregnancy termination. Differential changes in mean scores were determined by analysis of covariance (ANCOVA) and inter-group differences were assessed by ordinary least squares methods. RESULTS: Women who had experienced a miscarriage had more mental distress at 10 days and six months after the pregnancy termination than women who had undergone an abortion. However, women who had had a miscarriage exhibited significantly quicker improvement on IES scores for avoidance, grief, loss, guilt and anger throughout the observation period. Women who experienced induced abortion had significantly greater IES scores for avoidance and for the feelings of guilt, shame and relief than the miscarriage group at two and five years after the pregnancy termination (IES avoidance means: 3.2 vs 9.3 at T3, respectively, p < 0.001; 1.5 vs 8.3 at T4, respectively, p < 0.001). Compared with the general population, women who had undergone induced abortion had significantly higher HADS anxiety scores at all four interviews (p < 0.01 to p < 0.001), while women who had had a miscarriage had significantly higher anxiety scores only at T1 (p < 0.01). CONCLUSION: The course of psychological responses to miscarriage and abortion differed during the five-year period after the event. Women who had undergone an abortion exhibited higher scores during the follow-up period for some outcomes. The difference in the courses of responses may partly result from the different characteristics of the two pregnancy termination events

Robust ensemble-based multi-objective optimization

We consider robust ensemble-based multi-objective optimization using a hierarchical switching algorithm for combined long-term and short term water flooding optimization. We apply a modified formulation of the ensemble gradient which results in improved performance compared to earlier formulations. We also apply multi-dimensional scaling to visualize projections of the high-dimensional search space, to aid in understanding the complex nature of the objective function surface and the performance of the optimization algorithm. This provides insights into the quality of the gradient, and confirms the presence of ridges in the objective function surface which can be exploited for multi-objective optimization. We used a 18553-gridblock reservoir model of a channelized reservoir with 4 producers and 8 injectors. The controls were the flow rates in the injectors, and the long-term and short-term objective functions were undiscounted net present value (NPV) and highly discounted (25%) NPV respectively. We achieved an increase of 15.2% in the secondary objective for a decrease of 0.5% in the primary objective, averaged over 100 geological realizations. The total number of reservoir simulations was around 20000, which indicates the potential to use the ensemble optimization method for robust multi-objective optimization of medium-sized reservoir model