When AI models like Claude process words internally, they treat them as 'activation values,' which are long sequences of numbers that encode thoughts and are difficult to decipher. For many years, ...
Abstract: The backdoor attack poses a new security threat to deep neural networks (DNNs). The existing backdoor often relies on visible universal triggers to make the backdoored model malfunction, ...
Abstract: Hyperspectral anomaly detection (HAD) aims to identify targets that are significantly different from their surrounding background, employing an unsupervised paradigm. Recently, detectors ...
Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...
The ultimate goal of various fields is to directly generate molecules with desired properties, such as water-soluble molecules in drug development and molecules suitable for organic light-emitting ...
Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...
Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...
This repository provides code to accompany the paper: Greener JG, Moffat L and Jones DT, Design of metalloproteins and novel protein folds using variational autoencoders, Scientific Reports 8:16189, ...