As the use of Artificial Intelligence (AI) and Machine Learning (ML) expands to various industries, it is important to ensure trust in AI systems…
Browsing: Robustness
This article explores the concept of batch normalisation, a powerful technique used to address the challenges of training deep neural networks. It explains how…
Recent work has employed quantum-mechanical phenomena to defend against adversarial attacks in machine learning, spurring the development of the field of quantum adversarial machine…
Robustify is a GitHub repository focused on evaluating the effects of adding structurally conserving noise to data. It provides a comprehensive set of tools…
The Agentur für Innovation in der Cybersicherheit GmbH (Cyberagentur) has launched a five-year research project to increase the reliability and security of various AI…
Sam Mugel, Ph.D., CTO of Multiverse Computing, is exploring the use of quantum mechanics to enhance machine learning applications. This quantum-inspired enhancement, known as…
ChatGPT from OpenAI is an AI application that has reached an impressive level of maturity, capable of responding to questions with answers that are…
Ren Wang, an Assistant Professor at the Illinois Institute of Technology, has been awarded a two-year grant from the National Science Foundation’s Computer and…
This paper proposes a method for multi-object tracking using the High-Resolution Net (HRNet) as the baseline. The HRNet is used to learn high-resolution representations…
This paper presents a framework for testing and benchmarking the robustness of machine learning models by simulating biological sequences with errors. It introduces several…