These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.

In this work, we develop a new framework for designing experiments that are robust to model misspecification through generalised Bayesian inference. This repository contains the files needed to ...

ABSTRACT: Special education services are designed to provide tailored support for students with diverse learning needs, with the expectation of improving academic achievement. This study examines the ...

oLLM is a lightweight Python library built on top of Huggingface Transformers and PyTorch and runs large-context Transformers on NVIDIA GPUs by aggressively offloading weights and KV-cache to fast ...

Department of Biomedical Engineering, Tandon School of Engineering, New York University, New York, NY, United States Introduction: Leptin, primarily secreted by adipose tissue, is a critical hormone ...

ABSTRACT: This study investigates the persistent academic impacts of the Head Start program, a federal government-funded early childhood intervention, using data from the Early Childhood Longitudinal ...

Abstract: Naïve Bayesian inference enables classification or prediction of an event given observations of potentially contradictory evidences, and is particularly intriguing in power-limited contexts ...

Abstract: Accurate uncertainty quantification is critical for robust and trustworthy predictions in many real-world applications. Bayesian Neural Networks (BNNs) provide a principled approach for ...