124 citations · 249 across the 14 of their papers we have counts for
15 papers
Ensemble prosody prediction for expressive speech synthesis
Tian Huey Teh, Vivian Hu, Devang S Ram Mohan +7
Generating expressive speech with rich and varied prosody continues to be a challenge for Text-to-Speech. Most efforts have focused on sophisticated neural architectures intended t…
Machine learning assisted Bayesian model comparison: learnt harmonic mean estimator
Jason D. McEwen, Christopher G. R. Wallis, Matthew A. Price +1
We resurrect the infamous harmonic mean estimator for computing the marginal likelihood (Bayesian evidence) and solve its problematic large variance. The marginal likelihood is a k…
Ctrl-P: Temporal Control of Prosodic Variation for Speech Synthesis
Devang S Ram Mohan, Vivian Hu, Tian Huey Teh +6
Text does not fully specify the spoken form, so text-to-speech models must be able to learn from speech data that vary in ways not explained by the corresponding text. One way to r…
Scattering Networks on the Sphere for Scalable and Rotationally Equivariant Spherical CNNs
Jason D. McEwen, Christopher G. R. Wallis, Augustine N. Mavor-Parker
Convolutional neural networks (CNNs) constructed natively on the sphere have been developed recently and shown to be highly effective for the analysis of spherical data. While an e…
Efficient Generalized Spherical CNNs
Oliver J. Cobb, Christopher G. R. Wallis, Augustine N. Mavor-Parker +4
Many problems across computer vision and the natural sciences require the analysis of spherical data, for which representations may be learned efficiently by encoding equivariance…
On the effect of projections on convergence peak counts and Minkowski functionals
Zoe Vallis, Chris Wallis, Tom Kitching
The act of projecting data sampled on the surface of the celestial sphere onto a regular grid on the plane can introduce error and a loss of information. This paper evaluates the e…
Sparse Bayesian mass-mapping with uncertainties: hypothesis testing of structure
Matthew A. Price, Jason D. McEwen, Xiaohao Cai +2
A crucial aspect of mass-mapping, via weak lensing, is quantification of the uncertainty introduced during the reconstruction process. Properly accounting for these errors has been…
Exploring cosmic origins with CORE: mitigation of systematic effects
P. Natoli, M. Ashdown, R. Banerji +123
We present an analysis of the main systematic effects that could impact the measurement of CMB polarization with the proposed CORE space mission. We employ timeline-to-map simulati…
Exploring Cosmic Origins with CORE: Survey requirements and mission design
J. Delabrouille, P. de Bernardis, F. R. Bouchet +200
Future observations of cosmic microwave background (CMB) polarisation have the potential to answer some of the most fundamental questions of modern physics and cosmology. In this p…
Mapping dark matter on the celestial sphere with weak gravitational lensing
Christopher G. R. Wallis, Matthew A. Price, Jason D. McEwen +3
Convergence maps of the integrated matter distribution are a key science result from weak gravitational lensing surveys. To date, recovering convergence maps has been performed usi…
Wavelet-Based Segmentation on the Sphere
Xiaohao Cai, Christopher G. R. Wallis, Jennifer Y. H. Chan +1
Segmentation, a useful/powerful technique in pattern recognition, is the process of identifying object outlines within images. There are a number of efficient algorithms for segmen…
Sparse image reconstruction on the sphere: analysis and synthesis
Christopher G. R. Wallis, Yves Wiaux, Jason D. McEwen
We develop techniques to solve ill-posed inverse problems on the sphere by sparse regularisation, exploiting sparsity in both axisymmetric and directional scale-discretised wavelet…
Optimal scan strategies for future CMB satellite experiments
Christopher G. R. Wallis, Michael L. Brown, Richard A. Battye +1
The B-mode polarisation power spectrum in the Cosmic Microwave Background (CMB) is about four orders of magnitude fainter than the CMB temperature power spectrum. Any instrumental…
A new map-making algorithm for CMB polarisation experiments
Christopher G. R. Wallis, A. Bonaldi, Michael L. Brown +1
With the temperature power spectrum of the cosmic microwave background (CMB) at least four orders of magnitude larger than the B-mode polarisation power spectrum, any instrumental…
Removing beam asymmetry bias in precision CMB temperature and polarisation experiments
Christopher G. R. Wallis, Michael L. Brown, Richard A. Battye +2
Asymmetric beams can create significant bias in estimates of the power spectra from CMB experiments. With the temperature power spectrum many orders of magnitude stronger than the…