3 citations · 3 across the 2 of their papers we have counts for
2 papers
stat.ML2018★ 3 cited
Pymc-learn: Practical Probabilistic Machine Learning in Python
Daniel Emaasit
is a Python package providing a variety of state-of-the-art probabilistic models for supervised and unsupervised machine learning. It is inspired by $\textit{…
stat.ML2018
Capturing Structure Implicitly from Time-Series having Limited Data
Daniel Emaasit, Matthew Johnson
Scientific fields such as insider-threat detection and highway-safety planning often lack sufficient amounts of time-series data to estimate statistical models for the purpose of s…