194 citations · 543 across the 29 of their papers we have counts for
4 papers · 1 filter
Improving Explorability in Variational Inference with Annealed Variational Objectives
Chin-Wei Huang, Shawn Tan, Alexandre Lacoste +1
Despite the advances in the representational capacity of approximate distributions for variational inference, the optimization process can still limit the density that is ultimatel…
Uncertainty in Multitask Transfer Learning
Alexandre Lacoste, Boris Oreshkin, Wonchang Chung +3
Using variational Bayes neural networks, we develop an algorithm capable of accumulating knowledge into a prior from multiple different tasks. The result is a rich and meaningful p…
TADAM: Task dependent adaptive metric for improved few-shot learning
Boris N. Oreshkin, Pau Rodriguez, Alexandre Lacoste
Few-shot learning has become essential for producing models that generalize from few examples. In this work, we identify that metric scaling and metric task conditioning are import…
Neural Autoregressive Flows
Chin-Wei Huang, David Krueger, Alexandre Lacoste +1
Normalizing flows and autoregressive models have been successfully combined to produce state-of-the-art results in density estimation, via Masked Autoregressive Flows (MAF), and to…