1 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2021★ 1 cited
Probabilistic Attention for Interactive Segmentation
Prasad Gabbur, Manjot Bilkhu, Javier Movellan
We provide a probabilistic interpretation of attention and show that the standard dot-product attention in transformers is a special case of Maximum A Posteriori (MAP) inference. T…
cs.LG2020★ 1 cited
Probabilistic Transformers
Javier R. Movellan, Prasad Gabbur
We show that Transformers are Maximum Posterior Probability estimators for Mixtures of Gaussian Models. This brings a probabilistic point of view to Transformers and suggests exten…
stat.ML2015★ 1 cited
Variable and Fixed Interval Exponential Smoothing
Javier R. Movellan
Exponential smoothers are a simple and memory efficient way to compute running averages of time series. Here we define and describe practical properties of exponential smoothers fo…