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Bradley Gram-Hansen

Bradley Gram-Hansen

Probabilistic Programming, Monte Carlo Methods, Variational Inference, Computational Sustainability, Quantum Information

I am DPhil Student on the Autonomous Intelligent Machines and Systems (AIMS) program at the University of Oxford supervised by the wonderful Yee Whye Teh, Atılım Güneş Baydin, Phil Torr and Tom Rainforth. My research interests lie between the intersection of probabilistic programming, computational sustainability and Machine learning for societal uses. I am also interested in Quantum machine learning, as my background is in quantum information science.

Publications

2019

  • A. G. Baydin , L. Heinrich , W. Bhimji , B. Gram-Hansen , G. Louppe , L. Shao , K. Cranmer , F. Wood , Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model, Advances in Neural Information Processing Systems, NeurlPS 2019, 2019.
  • B. J. Gram-Hansen , P. Helber , I. Varatharajan , F. Azam , A. Coca-Castro , V. Kopackova , P. Bilinski , Mapping Informal Settlements in Developing Countries using Machine Learning and Low Resolution Multi-spectral Data, in Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019, 361–368.
  • B. Gram-Hansen , C. S. Witt , T. Rainforth , P. H. Torr , Y. W. Teh , A. G. Baydin , Hijacking Malaria Simulators with Probabilistic Programming, in International Conference on Machine Learning (ICML) AI for Social Good workshop (AI4SG), 2019.
  • A. G. Baydin , L. Shao , W. Bhimji , L. Heinrich , L. Meadows , J. Liu , A. Munk , S. Naderiparizi , B. Gram-Hansen , G. Louppe , . others , Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale, in Proceedings of the International Conference for High Performance Computing, SC 2019, 2019.
  • A. Blackwell , T. Kohn , M. Erwig , A. G. Baydin , L. Church , J. Geddes , A. Gordon , M. Gorinova , B. Gram-Hansen , N. Lawrence , . others , Usability of Probabilistic Programming Languages, in Psychology of Programming Interest Group 30th Annual Workshop, PPIG 2019, 2019.
  • Y. Zhou , B. Gram-Hansen , T. Kohn , T. Rainforth , H. Yang , F. Wood , A Low-Level Probabilistic Programming Language for Non-Differentiable Models, International Conference on Artificial Intelligence and Statistics (AISTATS), 2019.
    Project: bigbayes
  • Y. Zhou , B. Gram-Hansen , T. Kohn , T. Rainforth , H. Yang , F. Wood , LF-PPL: A Low-Level First Order Probabilistic Programming Language for Non-Differentiable Models, in The 22nd International Conference on Artificial Intelligence and Statistics, 2019, 148–157.
    Project: bigbayes

2018

  • P. Helber , B. Gram-Hansen , I. Varatharajan , F. Azam , A. Coca-Castro , V. Kopackova , P. Bilinski , Generating Material Maps to Map Informal Settlements, in NeurlPS workshop on Machine Learning for the Developing World (ML4DW), 2018.
  • B. Gram-Hansen , Y. Zhou , T. Kohn , T. Rainforth , H. Yang , F. Wood , Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities, in International Conference on Probabilistic Programming, 2018.

2015

  • B. J. Gram-Hansen , Electron-Proton Entanglement in the Hydrogen Atom, Master's thesis, 2015.

2014

  • B. J. Gram-Hansen , An Insight Into: Quantum Random Walks, Master's thesis, 2014.

Software

2019

  • Y. Zhou , B. Gram-Hansen , T. Kohn , T. Rainforth , H. Yang , F. Wood , A Low-Level Probabilistic Programming Language for Non-Differentiable Models, International Conference on Artificial Intelligence and Statistics (AISTATS). 2019.
    Project: bigbayes