Streaming sparse Gaussian process approximations

Sparse pseudo-point approximations for Gaussian process (GP) models provide a suite of methods that support deployment of GPs in the large data regime and enable analytic intractabilities to be sidestepped. However, the field lacks a principled method to handle streaming data in which both the posterior distribution over function values and the hyperparameter estimates are updated in an online fashion. The small number of existing approaches either use suboptimal hand-crafted heuristics for hyperparameter learning, or suffer from catastrophic forgetting or slow updating when new data arrive. This paper develops a new principled framework for deploying Gaussian process probabilistic models in the streaming setting, providing methods for learning hyperparameters and optimising pseudo-input locations. The proposed framework is assessed using synthetic and real-world datasets

Deep Gaussian processes for regression using approximate expectation propagation

Deep Gaussian processes (DGPs) are multi-layer hierarchical generalisations of Gaussian processes (GPs) and are formally equivalent to neural networks with multiple, infinitely wide hidden layers. DGPs are nonparametric probabilistic models and as such are arguably more flexible, have a greater capacity to generalise, and provide better calibrated uncertainty estimates than alternative deep models. This paper develops a new approximate Bayesian learning scheme that enables DGPs to be applied to a range of medium to large scale regression problems for the first time. The new method uses an approximate Expectation Propagation procedure and a novel and efficient extension of the probabilistic backpropagation algorithm for learning. We evaluate the new method for non-linear regression on eleven real-world datasets, showing that it always outperforms GP regression and is almost always better than state-of-the-art deterministic and sampling-based approximate inference methods for Bayesian neural networks. As a by-product, this work provides a comprehensive analysis of six approximate Bayesian methods for training neural networks

Gold- and Silver-Catalyzed Reactions of Propargylic Alcohols in the Presence of Protic Additives

A wide range of primary, secondary and tertiary propargylic alcohols undergo a Meyer–Schuster rearrangement to give enones at room temperature in the presence of a gold(I) catalyst and small quantities of MeOH or 4-methoxyphenylboronic acid. The syntheses of the enone natural products isoegomaketone and daphenone were achieved using this reaction as the key step. The rearrangement of primary propargylic alcohols can readily be combined in a one-pot procedure with the addition of a nucleophile to the resulting terminal enone, to give β-aryl, β-alkoxy, β-amino or β-sulfido ketones. Propargylic alcohols bearing an adjacent electron-rich aryl group can also undergo silver-catalyzed substitution of the alcohol with oxygen, nitrogen and carbon nucleophiles. This latter reaction was initially observed with a batch of gold catalyst that was probably contaminated with small quantities of silver salt

Black-Box α-divergence minimization

Black-box alpha (BB-α) is a new approximate inference method based on the minimization of α-divergences. BB-α scales to large datasets because it can be implemented using stochastic gradient descent. BB-α can be applied to complex probabilistic models with little effort since it only requires as input the likelihood function and its gradients. These gradients can be easily obtained using automatic differentiation. By changing the divergence parameter α, the method is able to interpolate between variational Bayes (VB) (α → 0) and an algorithm similar to expectation propagation (EP) (α = 1). Experiments on probit regression and neural network regression and classification problems show that BB-a with non-standard settings of α, such as α = 0.5, usually produces better predictions than with α → 0 (VB) or α = 1 (EP).JMHL acknowledges support from the Rafael del Pino Foundation. YL thanks the Schlumberger Foundation Faculty for the Future fellowship on supporting her PhD study. MR acknowledges support from UK Engineering and Physical Sciences Research Council (EPSRC) grant EP/L016516/1 for the University of Cambridge Centre for Doctoral Training, the Cambridge Centre for Analysis. TDB thanks Google for funding his European Doctoral Fellowship. DHL acknowledge support from Plan National I+D+i, Grant TIN2013-42351-P and TIN2015- 70308-REDT, and from Comunidad de Madrid, Grant S2013/ICE-2845 CASI-CAM-CM. RET thanks EPSRC grant #EP/L000776/1 and #EP/M026957/1

An economic evaluation of expanding hookworm control strategies to target the whole community.

Background: The WHO treatment guidelines for the soil-transmitted helminths (STH) focus on targeting children for the control of morbidity induced by heavy infections. However, unlike the other STHs, the majority of hookworm infections are harboured by adults. This untreated burden may have important implications for controlling both hookworm’s morbidity and transmission. This is particularly significant in the context of the increased interest in investigating STH elimination strategies. Methods We used a deterministic STH transmission model and parameter estimates derived from field epidemiological studies to evaluate the impact of child-targeted (2–14 year olds) versus community-wide treatment against hookworm in terms of preventing morbidity and the timeframe for breaking transmission. Furthermore, we investigated how mass treatment may influence the long-term programmatic costs of preventive chemotherapy for hookworm. Results: The model projected that a large proportion of the overall morbidity due to hookworm was unaffected by the current child-targeted strategy. Furthermore, driving worm burdens to levels low enough to potentially break transmission was only possible when using community-wide treatment. Due to these projected reductions in programme duration, it was possible for community-wide treatment to generate cost savings – even if it notably increases the annual distribution costs. Conclusions: Community-wide treatment is notably more cost-effective for controlling hookworm’s morbidity and transmission than the current child-targeted strategies and could even be cost-saving in many settings in the longer term. These calculations suggest that it is not optimum to treat using the same treatment strategies as other STH. Hookworm morbidity and transmission control require community-wide treatment.</p

Achieving elimination as a public health problem for schistosoma mansoni and S. haematobium: when is community-wide treatment required?

The World Health Organization (WHO) has set elimination as a public health problem (EPHP) as a goal for schistosomiasis. As the WHO treatment guidelines for schistosomiasis are currently under revision, we investigate whether school-based or community-wide treatment strategies are required for achieving the EPHP goal. In low- to moderate-transmission settings with good school enrolment, we find that school-based treatment is sufficient for achieving EPHP. However, community-wide treatment is projected to be necessary in certain high-transmission settings as well as settings with low school enrolment. Hence, the optimal treatment strategy depends on setting-specific factors such as the species present, prevalence prior to treatment, and the age profile of infection

Vaccination or mass drug administration against schistosomiasis: a hypothetical cost-effectiveness modelling comparison

Background Schistosomiasis is a neglected tropical disease, targeted by the World Health Organization for reduction in morbidity by 2020. It is caused by parasitic flukes that spread through contamination of local water sources. Traditional control focuses on mass drug administration, which kills the majority of adult worms, targeted at school-aged children. However, these drugs do not confer long-term protection and there are concerns over the emergence of drug resistance. The development of a vaccine against schistosomiasis opens the potential for control methods that could generate long-lasting population-level immunity if they are cost-effective. Methods Using an individual-based transmission model, matched to epidemiological data, we compared the cost-effectiveness of a range of vaccination programmes against mass drug administration, across three transmission settings. Health benefit was measured by calculating the heavy-intensity infection years averted by each intervention, while vaccine costs were assessed against robust estimates for the costs of mass drug administration obtained from data. We also calculated a critical vaccination cost, a cost beyond which vaccination might not be economically favorable, by benchmarking the cost-effectiveness of potential vaccines against the cost-effectiveness of mass drug administration, and examined the effect of different vaccine protection durations. Results We found that sufficiently low-priced vaccines can be more cost-effective than traditional drugs in high prevalence settings, and can lead to a greater reduction in morbidity over shorter time-scales. MDA or vaccination programmes that target the whole community generate the most health benefits, but are generally less cost-effective than those targeting children, due to lower prevalence of schistosomiasis in adults. Conclusions The ultimate cost-effectiveness of vaccination will be highly dependent on multiple vaccine characteristics, such as the efficacy, cost, safety and duration of protection, as well as the subset of population targeted for vaccination. However, our results indicate that if a vaccine could be developed with reasonable characteristics and for a sufficiently low cost, then vaccination programmes can be a highly cost-effective method of controlling schistosomiasis in high-transmission areas. The population-level immunity generated by vaccination will also inevitably improve the chances of interrupting transmission of the disease, which is the long-term epidemiological goal

The impact of complications and errors on surgeons

All surgical procedures carry with them the potential for adverse events. Dealing with the sequelae of the complications and errors that arise in the course of normal practice is therefore part and parcel of a surgeon’s working life. The challenges and stresses that this creates are now well recognised although surgical training has, until recently, done little to help surgeons prepare for such events and on-going professional and personal support is limited. This review shows that much of the research examining the impact of adverse events has been concentrated in healthcare systems outside of the UK, often markedly different to our own. With notable exceptions, sample sizes are often small and studies are often qualitative. While the latter provide rich and fascinating data, they may not always be representative, particularly if the focus is on serious errors where there is a risk of litigation. Despite the preponderance of complications, which are an acknowledged risk of surgical procedures, there is no research to date which has examined whether or not there are differences in the impact of complications versus errors on surgeons’ professional and personal lives. A national survey is currently planned to provide detailed information about the impact of adverse events – both complications and errors – which will map the way for better targeted support for surgeons to help them use their experiences to enhance their wellbeing and improve their practice

Towards a fair and transparent research participant compensation and reimbursement framework in Viet Nam

Background: Providing compensation for participants in clinical research is well established and whilst international guidelines exist, defining a context specific and fair compensation for participants in low resource settings is challenging due to ethical concerns and the lack of practical, national compensation and reimbursement frameworks. Methods: We reviewed OUCRU (Oxford University Clinical Research Unit) internal reimbursement documentation over a ten-year period and conducted a scoping literature review to expand our knowledge of compensation and reimbursement practices including ethical concerns. We developed a preliminary reimbursement framework that was presented to Community Advisory Boards (CAB) and clinical investigators to assess its applicability, fairness, and transparency. Results: The main topics discussed at the workshops centered on fairness and whether the reimbursements could be perceived as financial incentives. Other decisive factors in the decision making process were altruism and the loss of caregivers’ earnings. Investigators raised the issue of additional burdens, whereas the CAB members were focused on non-monetary elements such as the healthcare quality the patients would receive. All elements discussed were reviewed and where possible, incorporated into the final framework. Conclusion: Our new reimbursement framework provides a consistent, fair and transparent decision-making process and will be implemented across all future OUCRU clinical research in Viet Nam