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Alex Lamb

Researcher at Université de Montréal

Publications -  68
Citations -  8160

Alex Lamb is an academic researcher from Université de Montréal. The author has contributed to research in topics: Computer science & Artificial neural network. The author has an hindex of 23, co-authored 56 publications receiving 6549 citations. Previous affiliations of Alex Lamb include Johns Hopkins University.

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Theano: A Python framework for fast computation of mathematical expressions

Rami Al-Rfou, +111 more
TL;DR: The performance of Theano is compared against Torch7 and TensorFlow on several machine learning models and recently-introduced functionalities and improvements are discussed.
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Adversarially Learned Inference

TL;DR: The adversarially learned inference (ALI) model is introduced, which jointly learns a generation network and an inference network using an adversarial process and the usefulness of the learned representations is confirmed by obtaining a performance competitive with state-of-the-art on the semi-supervised SVHN and CIFAR10 tasks.
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Deep Learning for Classical Japanese Literature

TL;DR: This work introduces Kuz Kushiji-MNIST, a dataset which focuses on Kuzushiji (cursive Japanese), as well as two larger, more challenging datasets, KuzUSHiji-49 and Kuzushaiji-Kanji, which are intended to engage the machine learning community into the world of classical Japanese literature.
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Manifold Mixup: Better Representations by Interpolating Hidden States.

TL;DR: Manifold Mixup, a simple regularizer that encourages neural networks to predict less confidently on interpolations of hidden representations, improves strong baselines in supervised learning, robustness to single-step adversarial attacks, and test log-likelihood.