Hackaday

How LLMs Can Be Assisted To Do Arithmetic Correctly

One of the most hilarious things you can do with an LLM-based chatbot is to ask it to do calculations. If it’s a well-written ...
PNAS

Quantum advantage in variational Bayes inference

Quantum machine learning (QML) is an emerging research field that deals with quantum algorithms for data analysis. It is hoped that QML will yield practical demonstrations of quantum advantage by ...
Scientific Research Publishing

Variational Auto-Encoder and Speeded-Up Robust Features Hybrid Model for Anomaly Detection and Localization in Video Sequence with Scale Variation ()

Jomo Kenyatta University of Agriculture and Technology, Juja, Kiambu County, Kenya. Where KL denotes the Kullback-Leibler divergence, and p(z) is a prior distribution over the latent space (typically ...
IEEE

Distributed Variational Inference for Online Supervised Learning

Abstract: This article introduces a scalable distributed probabilistic inference algorithm for intelligent sensor networks, tackling challenges of continuous variables, intractable posteriors, and ...
IEEE

Variational Bayesian Inference Algorithms for Infinite Relational Model of Network Data

Abstract: Network data show the relationship among one kind of objects, such as social networks and hyperlinks on the Web. Many statistical models have been proposed for analyzing these data. For ...
GitHub

PyVBMC: Variational Bayesian Monte Carlo in Python

PyVBMC is a Python implementation of the Variational Bayesian Monte Carlo (VBMC) algorithm for posterior and model inference, previously implemented in MATLAB. VBMC is an approximate inference method ...
PNAS

Joint trajectory inference for single-cell genomics using deep learning with a mixture prior

We propose an approach for joint trajectory analysis of multiple single-cell sequencing data, combining Bayesian hierarchical models with variational autoencoders. Based on a coherent statistical ...