This repository contains the official implementation of the paper: "Uncertainty-Aware Out-of-Distribution Detection with Gaussian Processes" Deep neural networks (DNNs) often fail to handle ...

Global biodiversity is declining at an unprecedented rate, with agriculture as a major driver. There is mounting evidence that intercropping can increase insect biodiversity while maintaining or ...

Abstract: The long-term fluctuation of transmission loss in scatter propagation systems has been found to have a logarithmicnormal distribution. In other words, the scatter loss in decibels has ...

We propose GPS-Gaussian, a generalizable pixel-wise 3D Gaussian representation for synthesizing novel views of any unseen characters instantly without any fine-tuning ...

We have explored two approaches: a simple one based on independent, stationary Gaussian processes and a more advanced one relying on deep neural networks with autoencoders and convolutional layers. In ...

Persistent Link: https://ieeexplore.ieee.org/servlet/opac?punumber=4547466 ...

Khorram, F. , Pais, G. and Reyes, M. (2025) Assessing Joint Simulation and Estimation Approaches in Geometallurgical Modeling ...

Braskem’s improved financial position and declining interest rates signal growth. Read why BAK stock is a strong buy with ...

Researchers at the University of Michigan and colleagues at the Max Planck Institute for Astrophysics (MPA) used a ...

A new computational method gleans more information than its predecessors from maps showing how galaxies are clustered and threaded throughout the universe.

This important study investigates how hummingbird hawkmoths integrate stimuli from across their visual field to guide flight behavior. Cue conflict experiments provide solid evidence for an ...