BNN TRAINING WITH MINI-BATCH PARTICLE FLOW

Discussed herein are devices, systems, and methods for Bayesian neural network (BNN) training using mini-batch particle flow. A method for training a Bayesian neural network (BNN) using batched inputs and operating the trained BNN can include initializing particles such that each particle individual...

Full description

Saved in:
Bibliographic Details
Main Authors ALLERDT, Andrew C, SALPUKAS, Michael R, BAKER, Suzanne M
Format Patent
LanguageEnglish
French
German
Published 04.09.2024
Subjects
CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
PHYSICS
Online AccessGet full text

Cover

More Information
Summary:Discussed herein are devices, systems, and methods for Bayesian neural network (BNN) training using mini-batch particle flow. A method for training a Bayesian neural network (BNN) using batched inputs and operating the trained BNN can include initializing particles such that each particle individually represents pointwise values of respective NN parameters of NNs and such that the particles collectively represent a distribution of parameters of the BNN, optimizing, using min-batch training particle flow, the particles based on batches of inputs, resulting in optimized distributions for the parameters, determining a prediction distribution using the optimized distributions for the parameters and predictions from each of the NNs, and providing a marginalized distribution representative of the prediction distribution.
Bibliography:Application Number: EP20220812938