D.Sabbagh, P. Ablin, G.Varoquaux, A. Gramfort and D.A. Engemann. Manifold regression to predict from M/EEG signals without source model. Preprint.

P. Ablin, T.Moreau, M.Massias and A. Gramfort. Learning step sizes for unfolded sparse coding. Preprint.

P. Ablin, J.F. Cardoso and A. Gramfort. Beyond Pham’s algorithm for joint diagonalization. ESANN 2019.

Best student paper award

P. Ablin, D. Fagot, H. Wendt, A. Gramfort and C. Févotte. A Quasi-Newton algorithm on the orthogonal manifold for NMF with transform learning. ICASSP 2019.

P. Ablin, A. Gramfort, J.F. Cardoso and F. Bach.  Stochastic algorithms with desent guarantees for ICA.


P. Ablin, J.F. Cardoso and A. Gramfort. Accelerating Likelihood Optimization for ICA on Real Signals. LVA-ICA ’18.

Best student paper award

P. Ablin, J.F. Cardoso and A. Gramfort.  Faster ICA under orthogonal constraint.    ICASSP’18.

P. Ablin, J.F. Cardoso and A. Gramfort.  Faster independent component analysis by preconditioning with Hessian approximations.  Accepted for publication in IEEE-Transactions on Signal Processing (2017).

P. Ablin and K. Siddiqi. Detecting Myocardial Infarction Using Medial Surfaces. International Workshop on Statistical Atlases and Computational Models of the Heart (2015).