Zobrazeno 1 - 10
of 90
pro vyhledávání: '"Finlay, Chris"'
Autor:
Bianco, Michele, Giri, Sambit. K., Sharma, Rohit, Chen, Tianyue, Krishna, Shreyam Parth, Finlay, Chris, Nistane, Viraj, Denzel, Philipp, De Santis, Massimo, Ghorbel, Hatem
The low-frequency component of the upcoming Square Kilometre Array Observatory (SKA-Low) will be sensitive enough to construct 3D tomographic images of the 21-cm signal distribution during reionization. However, foreground contamination poses challen
Externí odkaz:
http://arxiv.org/abs/2408.16814
Radio interferometry calibration and Radio Frequency Interference (RFI) removal are usually done separately. Here we show that jointly modelling the antenna gains and RFI has significant benefits when the RFI follows precise trajectories, such as for
Externí odkaz:
http://arxiv.org/abs/2301.04188
Autor:
Finlay, Chris
Radio Frequency Interference (RFI) is a massive problem for radio observatories around the world. Due to the growth of telecommunications and air travel RFI is increasing exactly when the world's radio telescopes are increasing significantly in sensi
Externí odkaz:
http://hdl.handle.net/11427/33716
Recent work has shown that Neural Ordinary Differential Equations (ODEs) can serve as generative models of images using the perspective of Continuous Normalizing Flows (CNFs). Such models offer exact likelihood calculation, and invertible generation/
Externí odkaz:
http://arxiv.org/abs/2106.08462
Machine learning models are vulnerable to adversarial attacks. One approach to addressing this vulnerability is certification, which focuses on models that are guaranteed to be robust for a given perturbation size. A drawback of recent certified mode
Externí odkaz:
http://arxiv.org/abs/2010.02508
Autor:
Finlay, Chris, Bassett, Bruce A.
Multiple studies have suggested the spread of COVID-19 is affected by factors such as climate, BCG vaccinations, pollution and blood type. We perform a joint study of these factors using the death growth rates of 40 regions worldwide with both machin
Externí odkaz:
http://arxiv.org/abs/2007.05542
We present a deterministic method to compute the Gaussian average of neural networks used in regression and classification. Our method is based on an equivalence between training with a particular regularized loss, and the expected values of Gaussian
Externí odkaz:
http://arxiv.org/abs/2006.06061
We approach the problem of learning continuous normalizing flows from a dual perspective motivated by entropy-regularized optimal transport, in which continuous normalizing flows are cast as gradients of scalar potential functions. This formulation a
Externí odkaz:
http://arxiv.org/abs/2006.06033
Flagging of Radio Frequency Interference (RFI) is an increasingly important challenge in radio astronomy. We present R-Net, a deep convolutional ResNet architecture that significantly outperforms existing algorithms -- including the default MeerKAT R
Externí odkaz:
http://arxiv.org/abs/2005.08992
Training neural ODEs on large datasets has not been tractable due to the necessity of allowing the adaptive numerical ODE solver to refine its step size to very small values. In practice this leads to dynamics equivalent to many hundreds or even thou
Externí odkaz:
http://arxiv.org/abs/2002.02798