InfoQ

Google Researchers Propose Bayesian Teaching Method for Large Language Models

Google Research has proposed a training method that teaches large language models to approximate Bayesian reasoning by learning from the predictions of an optimal Bayesian system. The approach focuses ...
GitHub

Bayesian Modeling and Computation in Python

This repository contains the open-access version of the text and the code examples in the book. All of this can be more easily viewed at www.bayesiancomputationbook.com For the most up-to-date code ...
GitHub

gbc — Generative Bayesian Computation

Python companion package for the textbook: Generative Bayesian Computation: Quantile Neural Networks for Inference and Surrogates Nicholas Polson (University of Chicago) & Vadim Sokolov (George Mason ...
IEEE

Task-Oriented Computation Offloading for Edge Inference: An Integrated Bayesian Optimization and Deep Reinforcement Learning Framework

Abstract: Edge intelligence (EI) allows resource-constrained edge devices (EDs) to offload computation-intensive AI tasks (e.g., visual object detection) to edge servers (ESs) for fast execution.
IEEE

Scalable Quantum Approximate Optimisation with Adaptive Bayesian Dimensionality Reduction

Abstract: Quantum Approximate Optimisation Algorithm (QAOA) has emerged as a promising hybrid quantum-classical approach for tackling NP-hard combinatorial optimisation problems by combining quantum ...