activity
20122022
most citedImproving Photometric Redshift Estimation using GPz: size information, post processing and improved photometry

49 citations · 173 across the 21 of their papers we have counts for

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Showing 2017Show all

7 papers · 1 filter

astro-ph.GA201749 cited

Improving Photometric Redshift Estimation using GPz: size information, post processing and improved photometry

Zahra Gomes, Matt J. Jarvis, Ibrahim A. Almosallam +1

The next generation of large scale imaging surveys (such as those conducted with the Large Synoptic Survey Telescope and Euclid) will require accurate photometric redshifts in orde…

q-fin.TR20173 cited

Inferring agent objectives at different scales of a complex adaptive system

Dieter Hendricks, Adam Cobb, Richard Everett +2

We introduce a framework to study the effective objectives at different time scales of financial market microstructure. The financial market can be regarded as a complex adaptive s…

cs.AI2017

Novel Exploration Techniques (NETs) for Malaria Policy Interventions

Oliver Bent, Sekou L. Remy, Stephen Roberts +1

The task of decision-making under uncertainty is daunting, especially for problems which have significant complexity. Healthcare policy makers across the globe are facing problems…

cs.AI2017

Learning from lions: inferring the utility of agents from their trajectories

Adam D. Cobb, Andrew Markham, Stephen J. Roberts

We build a model using Gaussian processes to infer a spatio-temporal vector field from observed agent trajectories. Significant landmarks or influence points in agent surroundings…

astro-ph.IM201726 cited

Robust, open-source removal of systematics in Kepler data

S. Aigrain, H. Parviainen, S. Roberts +2

We present ARC2 (Astrophysically Robust Correction 2), an open-source Python-based systematics-correction pipeline to correct for the Kepler prime mission long cadence light curves…

stat.ML2017

A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes

Syed Ali Asad Rizvi, Stephen J. Roberts, Michael A. Osborne +1

In this paper we use Gaussian Process (GP) regression to propose a novel approach for predicting volatility of financial returns by forecasting the envelopes of the time series. We…