Annual meeting with IBC participants
On January 8th, we had our annual meeting with all participants: all of them were present.. We gave an update on the kinds of results reched through IBC and offered them a 3D printing of their cortex.
Category: Uncategorized
4 Internship positions available for Master students
Please take a look at http://team.inria.fr/parietal/job-offers/
Nistats 0.1a is out !
Please, see http://nistats.github.io for details. Thanks @MPerezGuevaraT for finalizing it. To give a try: `pip install nistats`
Nilearn 0.4 is out !
nilearn 0.4 release:https://t.co/Qs1GntYTGD Includes easy projection from volume to surface:https://t.co/F4IcBh6IZZ Making statistical learning on neuroimaging easier: pure Python, fast, and readable code. pic.twitter.com/nTrFneaTtP — Gael Varoquaux (@GaelVaroquaux) November 19, 2017
The IBC dataset is available on OpenfMRI !
See https://goo.gl/Bx4kvh
Multi-layer classification and dropout regularization permit transfer learning between fMRI datasets
https://t.co/lebGUZXuJc
PhD Defense of Elvis Dohmatob
Will take place on Tuesday, Sept 26th in Neurospin amphitheater. The thesis is entitled “Enhancement of functional brain connectome analysis by the use of deformable models in the estimation of spatial decompositions of the brain images”, and the committee includes: John Ashburner Gabriel Peyré Moritz Grosse-Wentrup Marc Schoenauer G. Varoquaux…
Parietal@CCN 2017
Jérôme Dockès is presenting a poster “Relating Brain Structures To Open-Ended Descriptions Of Cognition”: a rigorous machine learning setting for meta-analysis.
Decoding fMRI activity in the time domain improves classification performance
Now on HAL: https://hal.inria.fr/hal-01576641 Great work by @joaoloula.
Parietal@PRNI 2017: 2 oral presentations
Multi-output predictions from neuroimaging: assessing reduced-rank linear models Bertrand Thirion; Gael P Varoquaux; Mehdi Rahim* Towards a Faster Randomized Parcellation Based Inference Gael Varoquaux; Andres Hoyos-Idrobo*; Bertrand Thirion See https://sites.google.com/site/prni2017/home/program/
4 Internship positions available for Master students
Please take a look at http://team.inria.fr/parietal/job-offers/
Nistats 0.1a is out !
Please, see http://nistats.github.io for details. Thanks @MPerezGuevaraT for finalizing it. To give a try: `pip install nistats`
Nilearn 0.4 is out !
nilearn 0.4 release:https://t.co/Qs1GntYTGD Includes easy projection from volume to surface:https://t.co/F4IcBh6IZZ Making statistical learning on neuroimaging easier: pure Python, fast, and readable code. pic.twitter.com/nTrFneaTtP — Gael Varoquaux (@GaelVaroquaux) November 19, 2017
The IBC dataset is available on OpenfMRI !
See https://goo.gl/Bx4kvh
Multi-layer classification and dropout regularization permit transfer learning between fMRI datasets
https://t.co/lebGUZXuJc
PhD Defense of Elvis Dohmatob
Will take place on Tuesday, Sept 26th in Neurospin amphitheater. The thesis is entitled “Enhancement of functional brain connectome analysis by the use of deformable models in the estimation of spatial decompositions of the brain images”, and the committee includes: John Ashburner Gabriel Peyré Moritz Grosse-Wentrup Marc Schoenauer G. Varoquaux…
Parietal@CCN 2017
Jérôme Dockès is presenting a poster “Relating Brain Structures To Open-Ended Descriptions Of Cognition”: a rigorous machine learning setting for meta-analysis.
Decoding fMRI activity in the time domain improves classification performance
Now on HAL: https://hal.inria.fr/hal-01576641 Great work by @joaoloula.
Parietal@PRNI 2017: 2 oral presentations
Multi-output predictions from neuroimaging: assessing reduced-rank linear models Bertrand Thirion; Gael P Varoquaux; Mehdi Rahim* Towards a Faster Randomized Parcellation Based Inference Gael Varoquaux; Andres Hoyos-Idrobo*; Bertrand Thirion See https://sites.google.com/site/prni2017/home/program/
