This is a lightweight repository of bayesian neural network for PyTorch. @article{lee2022graddiv, title={Graddiv: Adversarial robustness of randomized neural networks via gradient diversity ...

The Bayesian method is the natural approach to inference, yet it is hidden from readers behind chapters of slow, mathematical analysis. The typical text on Bayesian inference involves two to three ...

This paper introduces the potential of intelligent Bayesian regularization backpropagation neuro computing (IBRBNC) for the precise estimation of state features of underwater passive object. The ...

The firm owned 3,655 shares of the scientific and technical instruments company’s stock after selling 56 shares during the period. DAVENPORT & Co LLC’s holdings in Badger Meter were worth $ ...

This paper uses Bayesian methods in conjunction with spatiotemporal and zoonotic data to evaluate the odds ratio for two hypotheses regarding the origin of the COVID-19 pandemic, namely, an accidental ...

The KAIST team employed the multi-objective Bayesian optimization machine learning ... withstanding a stress of 2.03 megapascals for every cubic meter per kilogram of its density, which is about ...

"I think when companies come in and dump their products in the United States, they should pay automatically, let's say a 10% tax." ...

Several automated software packages facilitate conducting NMA using either of two alternative approaches, Bayesian or frequentist frameworks. Researchers must choose a framework for conducting NMA ...

A statistical modelling method to produce predictions of seasonal streamflows. Application of the BJP method to streamflow forecasting was developed by the CSIRO. See the Seasonal Streamflow Forecast ...

Participants were randomly assigned (with the use of Bayesian response-adaptive randomization) to receive one of five combinations or standard therapy. The primary end point was a favorable ...