354 citations · 1.9k across the 38 of their papers we have counts for
6 papers · 1 filter
TensorFlow Distributions
Joshua V. Dillon, Ian Langmore, Dustin Tran +7
The TensorFlow Distributions library implements a vision of probability theory adapted to the modern deep-learning paradigm of end-to-end differentiable computation. Building on tw…
Fixing a Broken ELBO
Alexander A. Alemi, Ben Poole, Ian Fischer +3
Recent work in unsupervised representation learning has focused on learning deep directed latent-variable models. Fitting these models by maximizing the marginal likelihood or evid…
Watch Your Step: Learning Node Embeddings via Graph Attention
Sami Abu-El-Haija, Bryan Perozzi, Rami Al-Rfou +1
Graph embedding methods represent nodes in a continuous vector space, preserving information from the graph (e.g. by sampling random walks). There are many hyper-parameters to thes…
Jeffrey's prior sampling of deep sigmoidal networks
Lorien X. Hayden, Alexander A. Alemi, Paul H. Ginsparg +1
Neural networks have been shown to have a remarkable ability to uncover low dimensional structure in data: the space of possible reconstructed images form a reduced model manifold…
Motion Prediction Under Multimodality with Conditional Stochastic Networks
Katerina Fragkiadaki, Jonathan Huang, Alex Alemi +3
Given a visual history, multiple future outcomes for a video scene are equally probable, in other words, the distribution of future outcomes has multiple modes. Multimodality is no…
Light Microscopy at Maximal Precision
Matthew Bierbaum, Brian D. Leahy, Alexander A. Alemi +2
Microscopy is the workhorse of the physical and life sciences, producing crisp images of everything from atoms to cells well beyond the capabilities of the human eye. However, the…