Bradley Gram-Hansen

Bradley Gram-Hansen

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

I am 2nd year DPhil Student on the 3rd year of the Autonomous Intelligent Machines and Systems (AIMS) at the University of Oxford. I am currently supervised by Yee Whye Teh, Frank Wood and Phil Torr . My research interests lie in the intersection of probabilistic programming, physics and computational sustainability. I am also interested in Quantum machine learning.



  • B. 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, Proceedings of AAAI/ACM Conference on AI, Ethics, and Society, 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, to appear), 2019.
    Project: bigbayes


  • B. J. Gram-Hansen , Y. Zhou , T. Kohn , T. Rainforth , H. Yang , F. Wood , Discontinuous Hamiltonian Monte Carlo for Probabilistic Programs, The International Conference on Probabilistic Programming, 2018.
  • A. G. Baydin , L. Heinrich , W. Bhimji , B. J. Gram-Hansen , G. Louppe , L. Shao , K. Cranmer , F. Wood , . others , Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard Model, 2018.
  • P. Helber , B. J. Gram-Hansen , I. Varatharajan , F. Azam , A. Coca-Castro , V. Kopackova , P. Bilinski , Generating Material Maps to Map Informal Settlements, NeurIPS 2018 Workshop on Machine Learning for the Developing World, 2018.


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


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