By applying new methods of machine learning to quantum chemistry research, Heidelberg University scientists have made significant strides in computational chemistry. They have achieved a major ...
The CMS Collaboration has shown, for the first time, that machine learning can be used to fully reconstruct particle ...
Microelectromechanical systems (MEMS) electrothermal actuators are widely used in applications ranging from micro-optics and ...
Insulin resistance - when the body doesn't properly respond to insulin, a hormone that helps control blood glucose levels - ...
Abstract: Quantum Machine Learning (QML) has emerged as a promising frontier within artificial intelligence, offering enhanced data-driven modeling through quantum-augmented representation, ...
Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
This repo is the official PyTorch implementation of CVPR2025 paper "Language Guided Concept Bottleneck Models for Interpretable Continual Learning". We follow the framework of Pilot to implement this ...
One of the long-term goals of artificial intelligence (AI) is to build machines that can continually learn new knowledge from their experiences, ground these experiences in the physical world, and ...
Abstract: Federated Learning (FL) is a distributed machine learning paradigm where a central server coordinates the training of a global model across multiple decentralized clients. Most FL algorithms ...
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