Linear Algebra


  1. Posterior and Computational Uncertainty in Gaussian processes
    In Advances in Neural Information Processing Systems (NeurIPS) 2022


  1. Probabilistic Iterative Methods for Linear Systems
    Cockayne, Jon, Ipsen, Ilse CF, Oates, Chris J, and Reid, Tim W
    arXiv preprint arXiv:2012.12615 2020
  2. A Probabilistic Numerical Extension of the Conjugate Gradient Method
    Reid, Tim W, Ipsen, Ilse CF, Cockayne, Jon, and Oates, Chris J
    arXiv preprint arXiv:2008.03225 2020
  3. Probabilistic Linear Solvers for Machine Learning
    In Advances in Neural Information Processing Systems (NeurIPS) 2020


  1. A Bayesian conjugate gradient method (with discussion)
    Bayesian Analysis 2019


  1. Compression, inversion, and approximate PCA of dense kernel matrices at near-linear computational complexity
    Schäfer, Florian, Sullivan, T. J., and Owhadi, Houman
    arXiv:1706.02205 [cs, math] 2017
  2. Bayesian Inference of Log Determinants
    Fitzsimons, Jack, Cutajar, Kurt, Osborne, Michael, Roberts, Stephen, and Filippone, Maurizio
    In Uncertainty in Artificial Intelligence 2017


  1. Probabilistic Approximate Least-Squares
    Bartels, S., and Hennig, P.


  1. Stochastic determination of matrix determinants
    Dorn, Sebastian, and Enßlin, Torsten A.
    Phys. Rev. E 2015
  2. Probabilistic Interpretation of Linear Solvers
    Hennig, P.
    SIAM J on Optimization 2015


  1. Improving stochastic estimates with inference methods: Calculating matrix diagonals
    Selig, Marco, Oppermann, Niels, and Enßlin, Torsten A.
    Phys. Rev. E 2012