Towards nonlinear disentanglement in natural data with temporal sparse coding
We construct an unsupervised learning model that achieves nonlinear disentanglement of
underlying factors of variation in naturalistic videos. Previous work suggests that …
underlying factors of variation in naturalistic videos. Previous work suggests that …
Universal hidden monotonic trend estimation with contrastive learning
In this paper, we describe a universal method for extracting the underlying monotonic trend
factor from time series data. We propose an approach related to the Mann-Kendall test, a …
factor from time series data. We propose an approach related to the Mann-Kendall test, a …