Learning about multiple objects in images: Factorial learning without factorial search

We consider data which are images containing views of multiple objects

Learning Direct Optimization for scene understanding

We develop a Learning Direct Optimization (LiDO) method for the refinement of a latent variable model that describes input image x. Our goal is to explain a single image x with an interpretable 3D computer graphics model having scene graph latent variables z (such as object appearance, camera position). Given a current estimate of z we can render a prediction of the image g(z), which can be compared to the image x. The standard way to proceed is then to measure the error E(x, g(z)) between the two, and use an optimizer to minimize the error. However, it is unknown which error measure E would be most effective for simultaneously addressing issues such as misaligned objects, occlusions, textures, etc. In contrast, the LiDO approach trains a Prediction Network to predict an update directly to correct z, rather than minimizing the error with respect to z. Experiments show that our LiDO method converges rapidly as it does not need to perform a search on the error landscape, produces better solutions than error-based competitors, and is able to handle the mismatch between the data and the fitted scene model. We apply LiDO to a realistic synthetic dataset, and show that the method also transfers to work well with real images

Using the equivalent kernel to understand Gaussian process regression

The equivalent kernel [1] is a way of understanding how Gaussian process regression works for large sample sizes based on a continuum limit

Kernel multi-task learning using task-specific features

In this paper we are concerned with multitask learning when task-specific features are available. We describe two ways of achieving this using Gaussian process predictors: in the first method, the data from all tasks is combined into one dataset, making use of the task-specific features. In the second method we train specific predictors for each reference task, and then combine their predictions using a gating network. We demonstrate these methods on a compiler performance prediction problem, where a task is defined as predicting the speed-up obtained when applying a sequence of code transformations to a given program.

Vortex structure in d-density wave scenario of pseudogap

We investigate the vortex structure assuming the d-density wave scenario of the pseudogap. We discuss the profiles of the order parameters in the vicinity of the vortex, effective vortex charge and the local density of states. We find a pronounced modification of these quantities when compared to a purely superconducting case. Results have been obtained for a clean system as well as in the presence of a nonmagnetic impurity. We show that the competition between superconductivity and the density wave may explain some experimental data recently obtained for high-temperature superconductors. In particular, we show that the d-density wave scenario explains the asymmetry of the gap observed in the vicinity of the vortex core.Comment: 8 pages, 10 figure

Pseudopotential model of ultracold atomic collisions in quasi-one- and two-dimensional traps

We describe a model for s-wave collisions between ground state atoms in optical lattices, considering especially the limits of quasi-one and two dimensional axisymmetric harmonic confinement. When the atomic interactions are modelled by an s-wave Fermi-pseudopotential, the relative motion energy eigenvalues can easily be obtained. The results show that except for a bound state, the trap eigenvalues are consistent with one- and two- dimensional scattering with renormalized scattering amplitudes. For absolute scattering lengths large compared with the tightest trap width, our model predicts a novel bound state of low energy and nearly-isotropic wavefunction extending on the order of the tightest trap width.Comment: 9 pages, 8 figures; submitted to Phys. Rev.

Modelling frontal discontinuities in wind fields

A Bayesian procedure for the retrieval of wind vectors over the ocean using satellite borne scatterometers requires realistic prior near-surface wind field models over the oceans. We have implemented carefully chosen vector Gaussian Process models; however in some cases these models are too smooth to reproduce real atmospheric features, such as fronts. At the scale of the scatterometer observations, fronts appear as discontinuities in wind direction. Due to the nature of the retrieval problem a simple discontinuity model is not feasible, and hence we have developed a constrained discontinuity vector Gaussian Process model which ensures realistic fronts. We describe the generative model and show how to compute the data likelihood given the model. We show the results of inference using the model with Markov Chain Monte Carlo methods on both synthetic and real data

Balance on the Brain: a randomised controlled trial evaluating the effect of a multimodal exercise programme on physical performance, falls, quality of life and cognition for people with mild cognitive impairment—study protocol

Introduction: Exercise and physical activity have been shown to improve cognition for people living with mild cognitive impairment (MCI). There is strong evidence for the benefits of aerobic exercise and medium evidence for participating in regular strength training for people with MCI. However, people living with MCI fall two times as often as those without cognitive impairment and the evidence is currently unknown as to whether balance training for people with MCI is beneficial, as has been demonstrated for older people without cognitive impairment. The aim of this study is to determine whether a balance-focused multimodal exercise intervention improves balance and reduces falls for people with MCI, compared with a control group receiving usual care. Methods and analysis: This single blind randomised controlled trial (Balance on the Brain) will be offered to 396 people with MCI living in the community. The multimodal exercise intervention consists of two balance programmes and a walking programme to be delivered by physiotherapists over a 6-month intervention period. All participants will be followed up over 12 months (for the intervention group, this involves 6-month intervention and 6-month maintenance). The primary outcomes are (1) balance performance and (2) rate of falls. Physical performance, levels of physical activity and sedentary behaviour, quality of life and cognition are secondary outcomes. A health economic analysis will be undertaken to evaluate the cost-effectiveness of the intervention compared with usual care. Ethics and dissemination: Ethics approval has been received from the South Metropolitan Health Service Human Research Ethics Committee (HREC), Curtin University HREC and the Western Australia Department of Health HREC; and approval has been received to obtain data for health costings from Services Australia. The results will be disseminated through peer-review publications, conference presentations and online platforms

PTF11iqb: cool supergiant mass-loss that bridges the gap between Type IIn and normal supernovae

The supernova (SN) PTF11iqb was initially classified as a Type IIn event caught very early after explosion. It showed narrow Wolf–Rayet (WR) spectral features on day 2 (as in SN 1998S and SN 2013cu), but the narrow emission weakened quickly and the spectrum morphed to resemble Types II-L and II-P. At late times, H? exhibited a complex, multipeaked profile reminiscent of SN 1998S. In terms of spectroscopic evolution, we find that PTF11iqb was a near twin of SN 1998S, although with somewhat weaker interaction with circumstellar material (CSM) at early times, and stronger interaction at late times. We interpret the spectral changes as caused by early interaction with asymmetric CSM that is quickly (by day 20) enveloped by the expanding SN ejecta photosphere, but then revealed again after the end of the plateau when the photosphere recedes. The light curve can be matched with a simple model for CSM interaction (with a mass-loss rate of roughly 10?4 M? yr?1) added to the light curve of a normal SN II-P. The underlying plateau requires a progenitor with an extended hydrogen envelope like a red supergiant at the moment of explosion, consistent with the slow wind speed (<80?km?s?1) inferred from narrow H? emission. The cool supergiant progenitor is significant because PTF11iqb showed WR features in its early spectrum – meaning that the presence of such WR features does not necessarily indicate a WR-like progenitor. Overall, PTF11iqb bridges SNe IIn with weaker pre-SN mass-loss seen in SNe II-L and II-P, implying a continuum between these types