activity
20172020
most citedBreaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities

4 citations · 10 across the 5 of their papers we have counts for

collaborators

10 papers

cs.LG20202 cited

Bloom Origami Assays: Practical Group Testing

Louis Abraham, Gary Becigneul, Benjamin Coleman +3

We study the problem usually referred to as group testing in the context of COVID-19. Given n samples collected from patients, how should we select and test mixtures of samples to…

stat.ME20202 cited

Crackovid: Optimizing Group Testing

Louis Abraham, Gary Bécigneul, Bernhard Schölkopf

We study the problem usually referred to as group testing in the context of COVID-19. Given samples taken from patients, how should we select mixtures of samples to be tested,…

cs.LG2019

Noise Contrastive Variational Autoencoders

Octavian-Eugen Ganea, Yashas Annadani, Gary Bécigneul

We take steps towards understanding the "posterior collapse (PC)" difficulty in variational autoencoders (VAEs),~i.e. a degenerate optimum in which the latent codes become independ…

cs.LG20194 cited

Breaking the Softmax Bottleneck via Learnable Monotonic Pointwise Non-linearities

Octavian-Eugen Ganea, Sylvain Gelly, Gary Bécigneul +1

The Softmax function on top of a final linear layer is the de facto method to output probability distributions in neural networks. In many applications such as language models or t…

cs.CL2018

Poincaré GloVe: Hyperbolic Word Embeddings

Alexandru Tifrea, Gary Bécigneul, Octavian-Eugen Ganea

Words are not created equal. In fact, they form an aristocratic graph with a latent hierarchical structure that the next generation of unsupervised learned word embeddings should r…

cs.LG2018

Riemannian Adaptive Optimization Methods

Gary Bécigneul, Octavian-Eugen Ganea

Several first order stochastic optimization methods commonly used in the Euclidean domain such as stochastic gradient descent (SGD), accelerated gradient descent or variance reduce…