Geometrical Insights for Implicit Generative Modeling

Learning algorithms for implicit generative models can optimize a variety of criteria that measure how the data distribution differs from the implicit model distribution, including the Wasserstein distance, the Energy distance, and the Maximum Mean Discrepancy criterion. A careful look at the geometries induced by these distances on the space of probability measures reveals interesting differences. In particular, we can establish surprising approximate global convergence guarantees for the $1$-Wasserstein distance,even when the parametric generator has a nonconvex parametrization.Comment: this version fixes a typo in a definitio

The European Photon Imaging Camera on XMM-Newton: The MOS Cameras

The EPIC focal plane imaging spectrometers on XMM-Newton use CCDs to record the images and spectra of celestial X-ray sources focused by the three X-ray mirrors. There is one camera at the focus of each mirror; two of the cameras contain seven MOS CCDs, while the third uses twelve PN CCDs, defining a circular field of view of 30 arcmin diameter in each case. The CCDs were specially developed for EPIC, and combine high quality imaging with spectral resolution close to the Fano limit. A filter wheel carrying three kinds of X-ray transparent light blocking filter, a fully closed, and a fully open position, is fitted to each EPIC instrument. The CCDs are cooled passively and are under full closed loop thermal control. A radio-active source is fitted for internal calibration. Data are processed on-board to save telemetry by removing cosmic ray tracks, and generating X-ray event files; a variety of different instrument modes are available to increase the dynamic range of the instrument and to enable fast timing. The instruments were calibrated using laboratory X-ray beams, and synchrotron generated monochromatic X-ray beams before launch; in-orbit calibration makes use of a variety of celestial X-ray targets. The current calibration is better than 10% over the entire energy range of 0.2 to 10 keV. All three instruments survived launch and are performing nominally in orbit. In particular full field-of-view coverage is available, all electronic modes work, and the energy resolution is close to pre-launch values. Radiation damage is well within pre-launch predictions and does not yet impact on the energy resolution. The scientific results from EPIC amply fulfil pre-launch expectations.Comment: 9 pages, 11 figures, accepted for publication in the A&A Special Issue on XMM-Newto

Antidepressant drugs and generic counselling for treatment of major depression in primary care:randomised trial with patient preference arms

Objectives: To compare the efficacy of antidepressant drugs and generic counselling for treating mild to moderate depression in general practice. To determine whether the outcomes were similar for patients with randomly allocated treatment and those expressing a treatment preference.Design: Randomised controlled trial, with patient preference arms. Follow up at 8 weeks and 12 months and abstraction of GP case notes.Setting: 31 general practices in Trent region.Participants: Patients aged 18–70 who met research diagnostic criteria for major depression; 103 patients were randomised and 220 patients were recruited to the preference arms.Main outcome measures: Difference in mean Beck depression inventory score; time to remission; global outcome assessed by a psychiatrist using all data sources; and research diagnostic criteria.Results: At 12 months there was no difference between the mean Beck scores in the randomised arms. Combining the randomised and patient preference groups, the difference in Beck scores was 0.4 (95% confidence interval −2.7 to 3.5). Patients choosing counselling did better than those randomised to it (mean difference in Beck score 4.6, 0.0 to 9.2). There was no difference in the psychiatrist's overall assessment of outcome between any of the groups. 221/265 (83%) of participants with a known outcome had a remission. Median time to remission was shorter in the group randomised to antidepressants than the other three groups (2 months v 3 months). 33/221 (15%) patients had a relapse.Conclusions: Generic counselling seems to be as effective as antidepressant treatment for mild to moderate depressive illness, although patients receiving antidepressants may recover more quickly. General practitioners should allow patients to have their preferred treatment

Fast and Scalable Score-Based Kernel Calibration Tests

We introduce the Kernel Calibration Conditional Stein Discrepancy test (KCCSD test), a nonparametric, kernel-based test for assessing the calibration of probabilistic models with well-defined scores. In contrast to previous methods, our test avoids the need for possibly expensive expectation approximations while providing control over its type-I error. We achieve these improvements by using a new family of kernels for score-based probabilities that can be estimated without probability density samples, and by using a conditional goodness-of-fit criterion for the KCCSD test's U-statistic. We demonstrate the properties of our test on various synthetic settings

Hidden in Plain Sight: Subgroup Shifts Escape OOD Detection

The safe application of machine learning systems in healthcare relies on valid performance claims. Such claims are typically established in a clinical validation setting designed to be as close as possible to the intended use, but inadvertent domain or population shifts remain a fundamental problem. In particular, subgroups may be differently represented in the data distribution in the validation compared to the application setting. For example, algorithms trained on population cohort data spanning all age groups may be predominantly applied in elderly people. While these data are not “out-of distribution”, changes in the prevalence of different subgroups may have considerable impact on algorithm performance or will at least render original performance claims invalid. Both are serious problems for safely deploying machine learning systems. In this paper, we demonstrate the fundamental limitations of individual example out-of-distribution detection for such scenarios, and show that subgroup shifts can be detected on a population-level instead. We formulate population-level shift detection in the framework of statistical hypothesis testing and show that recent state-of-the-art statistical tests can be effectively applied to subgroup shift detection in a synthetic scenario as well as real histopathology images

Eyes on the Prize: Creating Lifelong Learners Through Engagement with Assessment

In his seminal RSA lecture, Sir Ken Robinson summed up the prevailing view of assessment as one where to every question, there is one answer… and it is at the back of the book (Robinson 2010). Assessment, in the world Robinson describes, is seen as summative and is populated with predetermined outcomes that students feel they have to meet

Thinking like a teacher: Is the early career framework the answer to early career teachers’ prayers?

It’s a declaration that every teacher educator has heard from their trainees: ‘I’ve passed all the teaching standards so now I am a teacher!’ The current structure of teacher education encourages the view that training is a series of experiences that, once completed, provide confirmation of competency rather than a construction of a robust and well rooted professional identity that we identified in a previous blog post (Wolstencroft & Gretton, 2020). Since the articulation of required teacher knowledge was captured in the form of teacher standards, it has been assumed that knowledge occurs at the point of performance (Verran et al., 2007), something which may not be wholly true as these performances must be consistently re-enacted into their own practice to demonstrate that any real learning has occurred (Tenenberg, 2016)

When the subject becomes the object: Redefining the teacher standards as learner standards

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