Publications

Journal papers and preprints

  • Moews, B. et al. (2019), “Lagged correlation-based deep learning for directional trend change prediction in financial time series”, Expert Systems with Applications, Vol. 120, pp. 197-206 (journal | arXiv)

  • Moews, B. et al. (2018), “Stress testing the dark energy equation of state imprint on supernova data”, submitted to Physical Review D - Particles, Fields, Gravitation, and Cosmology (arXiv)

  • Fussell, L. and Moews, B. (2018), “Forging new worlds: High-resolution synthetic galaxies with chained generative adversarial networks”, submitted to Monthly Notices of the Royal Astronomical Society (arXiv)

  • Cantat-Gaudin, T. et al. (2018), “Gaia DR2 unravels incompleteness of nearby cluster population: New open clusters in the direction of Perseus”, submitted to Astronomy & Astrophysics (arXiv)

Conference presentations

  • Talk: “Deep learning for portfolio risk and financial economics: Investigating trend change predictability through lagged correlations”, 30th European Conference on OR (EURO 2019), Dublin, Ireland, June 23-26 2019

  • Talk: “What we might miss: Stress-testing measurements of dark energy”, 5th Joint Meeting of the German Consortium in Statistics (DAGStat 2019), Munich, Germany, March 18-22 2019

  • Talk: “Cosmology and beyond: Solutions for high-dimensional parameter estimation”, The Data Lab - Data Innovation in Scotland (DataTech19), Edinburgh, UK, March 14 2019

  • Talk: “Synthetic galaxies with chained deep learning models”, 15th Durham-Edinburgh eXtragalactic Workshop (DEX-XV), Edinburgh, UK, January 7-8 2019

  • Talk: “Massively parallel iterative Bayesian nonparametrics for cosmological parameter estimation”, Royal Statistical Society 2018 International Conference (RSS 2018), Cardiff, UK, September 3-6 2018

  • Talk: “High-dimensional posterior sampling with expensive likelihoods”, International Society for Bayesian Analysis 2018 World Meeting (ISBA 2018), Edinburgh, UK, June 24-29 2018

  • Poster: “Gaussbock: Fast parallel-iterative cosmological parameter estimation”, Statistical Challenges in 21st Century Cosmology (Cosmo21), Valencia, Spain, May 22-25 2018

  • Talk: “Non-parametric Bayesian methods for cosmological parameter estimation”, Statistical Challenges for Large-Scale Structure in the Era of LSST (SCLSS), Oxford, UK, April 18-20 2018