Examen de l'an dernier
- 2016-2017 AIC_DL_Exam_16.pdf
Pointeurs
- Vidéos des cours de Hugo Larochelle, accessibles ici. Voir également les informations détaillées plus bas.
- Cours de Yann Le Cun au Collège de France
14 nov. apres-midi AA
Généralités NN_2017_Cours1.pdf22 nov. matin AA
backprop29 nov. matin AA
regularisation et dropout6 dec. matin AA
deep learning13 dec. matin
Pas de cours / TP : SGD, Adagrad, ...10 jan. matin
- Pas cours
- TP à 10h45
17 jan. matin (2 cours) MS
- Cours Deep_VAE_GAN.pdf
1er février apres-midi - Attention changement de date !
présentation articles
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Attention Is All You Need, Mohamed Ali Darghouth et Walid Belrhalmia. - Prototypical Networks for Few-shot Learning, NIPS 2017
- A Bayesian Data Augmentation Approach for Learning Deep Models, NIPS 2017
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Understanding deep learning requires rethinking generalization, Eden BELOUADAH et Mariem Bouhaha - Active Bias: Training More Accurate Neural Networks by Emphasizing High Variance Samples, NIPS 2017
- Bayesian Compression for Deep Learning, NIPS 17
- Gradient Descent Can Take Exponential Time to Escape Saddle Points, NIPS 17
- When Cyclic Coordinate Descent Beats Randomized Coordinate Descent, NIPS 17
- Variance-based Regularization with Convex Objectives, NIPS 17
- Convergent Learning: Do different neural networks learn the same representations?
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Learning Activation Functions to Improve Deep Neural Networks -
Neural Machine Translation by Jointly Learning to Align and Translate, Taycir Yahmed, ?? - Auto-Encoding Variational Bayes
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Dual Learning for Machine Translation, Louis Trouche et Warren Pons -
Rationalizing Neural Predictions, Chloé Mercier et Julien Louis -
Visualizing and Understanding Neural Models in NLP, Amin Biad, Ghiles Sidi Said - Generating Sequences With Recurrent Neural Networks
- Wavenet: A Generative Model for Raw Audio
- Practical Variational Inference for Neural Networks
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MobileNets, Ludovic Kun -
DeepBach: a Steerable Model for Bach Chorales Generation, Adrien Pavao, Eléonore Bartenlian