Congrats Ravnoor for being featured on Neurology Today for your amazing work on "Detection of MRI-negative focal cortical dysplasia using uncertainty-informed Bayesian deep learning: A multicentre validation study" @ravnoor#AES2019@NeurologyToday
https://t.co/KAiHYLVOxS
Check out the latest preprint by @jordandekraker: Hippocampal morphology and cytoarchitecture in the 3D BigBrain. Privilege to be involved in this work with Kayla Ferko, @neuroak, and Stefan Kohler. @BMI_WesternU@Brains_CAN https://t.co/jDyKM7xzgd
Last call for the @IlaeWeb International Training Course on Neuroimaging of Epilepsy, May 16-19, 2019 at @TheNeuro_MNI@bic_mni, Montreal Canada.
Registration: https://t.co/7M1f0BF2oO
Check out our most recent gradient paper ... in BABIES !!! Multiscale associations between large-scale functional organization and intracortical myelin, superficial white matter, and thalamo-cortical connectivity already present at birth 👶🏻 Here >> https://t.co/FytjtsgpA0
There are many ways to visualize data - how do we know which one to pick?
@FT Visual Vocabulary: Vega Edition - https://t.co/kpMUW1byEZ helps you pick one.
Give it a spin! Credits @ftdata@VizWizBI@vega_vis@Gramener#dataviz 1/n
I often joke that my contributions to science are all the papers that will never exist or be published. But in the mean time will my career survive the short run?
most common neural net mistakes: 1) you didn't try to overfit a single batch first. 2) you forgot to toggle train/eval mode for the net. 3) you forgot to .zero_grad() (in pytorch) before .backward(). 4) you passed softmaxed outputs to a loss that expects raw logits. ; others? :)
My notes from @AndrewYNg excellent deep learning specialization on Coursera (https://t.co/SdzM1S9gA2)
Yay! finally finished it
Full notes on slideshare:
https://t.co/XuuRGgq39Z