GitHub

uqlm: Uncertainty Quantification for Language Models

UQLM provides a suite of response-level scorers for quantifying the uncertainty of Large Language Model (LLM) outputs. Each scorer returns a confidence score between 0 and 1, where higher scores ...
GitHub

Pull requests: teotsiftsis/Synthetic-Data-Generation-for-Classification-Model

Pull requests help you collaborate on code with other people. As pull requests are created, they’ll appear here in a searchable and filterable list. To get started, you should create a pull request.
IEEE

Probabilistic power flow considering variable bandwidth kernel density estimation for traction substation loads of high-speed railways

Abstract: A probabilistic power flow method considering variable bandwidth kernel density estimation (VKDE) for traction substation loads of high-speed railways is proposed. A variable bandwidth ...
IEEE

Jitter analysis based on kernel density estimation and dual-dirac

Abstract: Accurate jitter analysis is critical for next-generation I/O designs. In this paper, a method to separate deterministic jitter (DJ) and random jitter (RJ ...