13 citations · 19 across the 2 of their papers we have counts for
2 papers
stat.ML2018★ 13 cited
Neural Likelihoods via Cumulative Distribution Functions
Pawel Chilinski, Ricardo Silva
We leverage neural networks as universal approximators of monotonic functions to build a parameterization of conditional cumulative distribution functions (CDFs). By the applicatio…
stat.ML2016★ 6 cited
Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages
Yin Cheng Ng, Pawel Chilinski, Ricardo Silva
Factorial Hidden Markov Models (FHMMs) are powerful models for sequential data but they do not scale well with long sequences. We propose a scalable inference and learning algorith…