Oct. 4, 2023, 3:23 a.m. | Synced

Synced syncedreview.com

A NNAISENSE research team introduces a novel class of generative models known as Bayesian Flow Networks (BFNs). These BFNs combine the power of Bayesian inference with neural networks in an iterative modeling process, enabling successful application to continuous, discretized, and discrete data while maintaining competitive performance.


The post NNAISENSE’s New Class of Generative Model: Bayesian Flow Networks Break Barriers in Handing Discrete Data first appeared on Synced.

ai application artificial intelligence bayesian bayesian deep learning bayesian inference continuous data deep-neural-networks enabling flow generative generative-model generative models inference iterative machine learning machine learning & data science ml modeling networks neural networks nnaisense novel power process research research team team technology

More from syncedreview.com / Synced

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Business Data Scientist, gTech Ads

@ Google | Mexico City, CDMX, Mexico

Lead, Data Analytics Operations

@ Zocdoc | Pune, Maharashtra, India