Neural Variational Inference For Estimating Uncertainty in Knowledge Graph Embeddings

Recent advances in Neural Variational Inference allowed for a renaissance in latent variable models in a variety of domains involving high-dimensional data. While traditional variational methods derive an analytical approximation for the intractable distribution over the latent variables, here we construct an inference network conditioned on the symbolic representation of entities and relation types in the Knowledge Graph, to provide the variational distributions. The new framework results in a highly-scalable method. Under a Bernoulli sampling framework, we provide an alternative justification for commonly used techniques in large-scale stochastic variational inference, which drastically reduce training time at a cost of an additional approximation to the variational lower bound. We introduce two models from this highly scalable probabilistic framework, namely the Latent Information and Latent Fact models, for reasoning over knowledge graph-based representations. Our Latent Information and Latent Fact models improve upon baseline performance under certain conditions. We use the learnt embedding variance to estimate predictive uncertainty during link prediction, and discuss the quality of these learnt uncertainty estimates. Our source code and datasets are publicly available online at https://github.com/alexanderimanicowenrivers/Neural-Variational-Knowledge-Graphs.Comment: Accepted at IJCAI 19 Neural-Symbolic Learning and Reasoning Worksho

Screen-based media use clusters are related to other activity behaviours and health indicators in adolescents

Background: Screen-based media (SBM) occupy a considerable portion of young peoples’ discretionary leisure time. The aim of this paper was to investigate whether distinct clusters of SBM use exist, and if so, to examine the relationship of any identified clusters with other activity/sedentary behaviours and physical and mental health indicators.Methods: The data for this study come from 643 adolescents, aged 14 years, who were participating in the longitudinal Western Australian Pregnancy Cohort (Raine) Study through May 2003 to June 2006. Time spent on SBM, phone use and reading was assessed using the Multimedia Activity Recall for Children and Adults. Height, weight, muscle strength were measured at a clinic visit and the adolescents also completed questionnaires on their physical activity and psychosocial health. Latent class analysis (LCA) was used to analyse groupings of SBM use.Results: Three clusters of SBM use were found; C1 ‘instrumental computer users’ (high email use, general computer use), C2 ‘multi-modal e-gamers’ (both high console and computer game use) and C3 ‘computer e-gamers’ (high computer game use only). Television viewing was moderately high amongst all the clusters. C2 males took fewer steps than their male peers in C1 and C3 (-13,787/week, 95% CI: -4619 to -22957, p = 0.003 and -14,806, 95% CI: -5,306 to -24,305, p = 0.002) and recorded less MVPA than the C1 males (-3.5 h, 95% CI: -1.0 to -5.9, p = 0.005). There was no difference in activity levels between females in clusters C1 and C3.Conclusion: SBM use by adolescents did cluster and these clusters related differently to activity/sedentary behaviours and both physical and psychosocial health indicators. It is clear that SBM use is not a single construct and future research needs to take consideration of this if it intends to understand the impact SBM has on health

The Surface Array planned for IceCube-Gen2

IceCube-Gen2, the extension of the IceCube Neutrino Observatory, will feature three main components: an optical array in the deep ice, a large-scale radio array in the shallow ice and firn, and a surface detector above the optical array. Thus, IceCube-Gen2 will not only be an excellent detector for PeV neutrinos, but also constitutes a unique setup for the measurement of cosmic-ray air showers, where the electromagnetic component and low-energy muons are measured at the surface and high-energy muons are measured in the ice. As for ongoing enhancement of IceCube’s current surface array, IceTop, we foresee a combination of elevated scintillation and radio detectors for the Gen2 surface array, aiming at high measurement accuracy for air showers. The science goals are manifold: The in-situ measurement of the cosmic-ray flux and mass composition, as well as more thorough tests of hadronic interaction models, will improve the understanding of muons and atmospheric neutrinos detected in the ice, in particular, regarding prompt muons. Moreover, the surface array provides a cosmic-ray veto for the in-ice detector and contributes to the calibration of the optical and radio arrays. Last but not least, the surface array will make major contributions to cosmic-ray science in the energy range of the transition from Galactic to extragalactic sources. The increased sensitivities for photons and for cosmic-ray anisotropies at multi-PeV energies provide a chance to solve the puzzle of the origin of the most energetic Galactic cosmic rays and will serve IceCube’s multimessenger mission

Mechanical design of the optical modules intended for IceCube-Gen2

IceCube-Gen2 is an expansion of the IceCube neutrino observatory at the South Pole that aims to increase the sensitivity to high-energy neutrinos by an order of magnitude. To this end, about 10,000 new optical modules will be installed, instrumenting a fiducial volume of about 8 km3. Two newly developed optical module types increase IceCube’s current sensitivity per module by a factor of three by integrating 16 and 18 newly developed four-inch PMTs in specially designed 12.5-inch diameter pressure vessels. Both designs use conical silicone gel pads to optically couple the PMTs to the pressure vessel to increase photon collection efficiency. The outside portion of gel pads are pre-cast onto each PMT prior to integration, while the interiors are filled and cast after the PMT assemblies are installed in the pressure vessel via a pushing mechanism. This paper presents both the mechanical design, as well as the performance of prototype modules at high pressure (70 MPa) and low temperature (−40∘C), characteristic of the environment inside the South Pole ice