GitHub

A library for Bayesian neural network layers and uncertainty estimation in Deep Learning

Bayesian-Torch is a library of neural network layers and utilities extending the core of PyTorch to enable Bayesian inference in deep learning models to quantify principled uncertainty estimates in ...
The New York Times

Chatbots Can Go Into a Delusional Spiral. Here’s How It Happens.

Over 21 days of talking with ChatGPT, an otherwise perfectly sane man became convinced that he was a real-life superhero. We analyzed the conversation. By Kashmir Hill and Dylan Freedman Kashmir Hill ...
GitHub

Recursive logic for processing drop tables (implementation example)

I'll be brief. I need to be able to get 1 item from 2 sets of items and drop them together. Let's say there are 3 items in each set and we need to ensure that 1 item drops from the first set and 1 ...
Scientific Research Publishing

Bayesian Interval Estimation of the Prevalence Rate Using Pool Testing Strategy with Retesting ()

Mathematics Department, Egerton University, Njoro Nakuru, Kenya. Bayesian techniques have been applied in many epidemiological settings, such as disease monitoring, outbreak simulation, and prevalence ...
Hacker

Bayesian Power and Error Estimation in Survival Trials Using BayesPPDSurv

We consider the high-risk melanoma trial design application in Psioda and Ibrahim (2019), and demonstrate how BayesPPDSurv can be used for coefficient estimation as ...
IEEE

Quaternion Information Filters With Inaccurate Measurement Noise Covariance: A Variational Bayesian Method

Abstract: Quaternion Kalman filters (QKFs) are designed for state estimation in three-dimensional (3-D) space. To simplify initialization, this paper focuses on the quaternion information filter (QIF) ...
C&EN

ProcessOptimizer, an Open-Source Python Package for Easy Optimization of Real-World Processes Using Bayesian Optimization: Showcase of Features and Example of Use

ProcessOptimizer is a Python package designed to provide easy access to advanced machine learning techniques, specifically Bayesian optimization using, e.g., Gaussian processes. Aimed at ...
science.psu

A strategy to avoid particle depletion in recursive Bayesian inference

Recursive Bayesian inference, in which posterior beliefs are updated in light of accumulating data, is a tool for implementing Bayesian models in applications with streaming and/or very large data ...