The analysts working on AI projects have a crucial question: How will the interventions brought about by the AI cause the desired outcomes? To date, only about 20% of companies have managed to scale ...
Google’s Gemma series continues to throw up all kinds of interesting models. The latest is Magenta RealTime 2 (MRT2), an open-weights model ...
A representation of the cause-effect mechanism is needed to enable artificial intelligence to represent how the world works. Bayesian Networks (BNs) have proven to be an effective and versatile tool ...
There are many implemented methods to perform causal inference when your intervention of interest is binary, but few methods exist to handle continuous treatments. This is unfortunate because there ...
Confocal imaging maps the intracellular distribution of Cy5-labeled polyplexes, providing estimates of the proportion of pDNA partitioned between the cytoplasmic and nuclear regions. The lead polymer ...
We perceive our environment through multiple independent sources of sensory input. The brain is tasked with deciding whether multiple signals are produced by the same or different events (i.e., solve ...
This repository contains all the necessary data and custom Python scripts to reproduce the results in the paper "Machine Learning–Aided Causal Inference Framework for Environmental Data Analysis: A ...
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