K Friston

Summary

Affiliation: University College London
Country: UK

Publications

  1. request reprint
    Friston K, Penny W. Posterior probability maps and SPMs. Neuroimage. 2003;19:1240-9 pubmed
    ..We then compare Bayesian and classical inference through the equivalent PPMs and SPMs testing for the same effect in the same data. ..
  2. request reprint
    Friston K, Mattout J, Trujillo Barreto N, Ashburner J, Penny W. Variational free energy and the Laplace approximation. Neuroimage. 2007;34:220-34 pubmed
    ..Finally, we also consider, briefly, dynamic models and how these inform the regularisation of free energy ascent schemes, like EM and ReML. ..
  3. request reprint
    Friston K, Harrison L, Daunizeau J, Kiebel S, Phillips C, Trujillo Barreto N, et al. Multiple sparse priors for the M/EEG inverse problem. Neuroimage. 2008;39:1104-20 pubmed
    ..This means the approach automatically selects either a sparse or a distributed model, depending on the data. The scheme is compared with conventional applications of Bayesian solutions to quantify the improvement in performance. ..
  4. Friston K, Trujillo Barreto N, Daunizeau J. DEM: a variational treatment of dynamic systems. Neuroimage. 2008;41:849-85 pubmed publisher
    ..Furthermore, it provides for dual and triple inferences on a system's states, parameters and hyperparameters using exactly the same principles. We refer to this approach as dynamic expectation maximisation (DEM). ..
  5. Friston K, Mattout J, Kilner J. Action understanding and active inference. Biol Cybern. 2011;104:137-60 pubmed publisher
    ..Our results affirm that a Bayes-optimal approach provides a principled framework, which accommodates current thinking about the mirror-neuron system. Furthermore, it endorses the general formulation of action as active inference. ..

Detail Information

Publications5

  1. request reprint
    Friston K, Penny W. Posterior probability maps and SPMs. Neuroimage. 2003;19:1240-9 pubmed
    ..We then compare Bayesian and classical inference through the equivalent PPMs and SPMs testing for the same effect in the same data. ..
  2. request reprint
    Friston K, Mattout J, Trujillo Barreto N, Ashburner J, Penny W. Variational free energy and the Laplace approximation. Neuroimage. 2007;34:220-34 pubmed
    ..Finally, we also consider, briefly, dynamic models and how these inform the regularisation of free energy ascent schemes, like EM and ReML. ..
  3. request reprint
    Friston K, Harrison L, Daunizeau J, Kiebel S, Phillips C, Trujillo Barreto N, et al. Multiple sparse priors for the M/EEG inverse problem. Neuroimage. 2008;39:1104-20 pubmed
    ..This means the approach automatically selects either a sparse or a distributed model, depending on the data. The scheme is compared with conventional applications of Bayesian solutions to quantify the improvement in performance. ..
  4. Friston K, Trujillo Barreto N, Daunizeau J. DEM: a variational treatment of dynamic systems. Neuroimage. 2008;41:849-85 pubmed publisher
    ..Furthermore, it provides for dual and triple inferences on a system's states, parameters and hyperparameters using exactly the same principles. We refer to this approach as dynamic expectation maximisation (DEM). ..
  5. Friston K, Mattout J, Kilner J. Action understanding and active inference. Biol Cybern. 2011;104:137-60 pubmed publisher
    ..Our results affirm that a Bayes-optimal approach provides a principled framework, which accommodates current thinking about the mirror-neuron system. Furthermore, it endorses the general formulation of action as active inference. ..