40 citations · 242 across the 20 of their papers we have counts for
5 papers · 1 filter
Investigating Biases in Textual Entailment Datasets
Shawn Tan, Yikang Shen, Chin-wei Huang +1
The ability to understand logical relationships between sentences is an important task in language understanding. To aid in progress for this task, researchers have collected datas…
Note on the bias and variance of variational inference
Chin-Wei Huang, Aaron Courville
In this note, we study the relationship between the variational gap and the variance of the (log) likelihood ratio. We show that the gap can be upper bounded by some form of disper…
vGraph: A Generative Model for Joint Community Detection and Node Representation Learning
Fan-Yun Sun, Meng Qu, Jordan Hoffmann +2
This paper focuses on two fundamental tasks of graph analysis: community detection and node representation learning, which capture the global and local structures of graphs, respec…
Stochastic Neural Network with Kronecker Flow
Chin-Wei Huang, Ahmed Touati, Pascal Vincent +3
Recent advances in variational inference enable the modelling of highly structured joint distributions, but are limited in their capacity to scale to the high-dimensional setting o…
Hierarchical Importance Weighted Autoencoders
Chin-Wei Huang, Kris Sankaran, Eeshan Dhekane +2
Importance weighted variational inference (Burda et al., 2015) uses multiple i.i.d. samples to have a tighter variational lower bound. We believe a joint proposal has the potential…