Feb 20, 2024 · Machine learning uses data to teach AI systems to imitate the way that humans learn. They can find the signal in the noise of big data, helping businesses improve their operations. We’ve …

May 25, 2025 · Quantum machine learning (QML) is a rapidly growing field that combines quantum computing principles with traditional machine learning. It seeks to revolutionize machine learning by …

Oct 5, 2023 · Part of the Linux Foundation, PyTorch is a machine-learning framework that ties together software and hardware to let users run AI workloads in the hybrid cloud. One of PyTorch’s key …

The IBM Research blog is the home for stories told by the researchers, scientists, and engineers inventing What’s Next in science and technology.

Sep 19, 2018 · We are pleased to announce AI Fairness 360 (AIF360), a comprehensive open-source toolkit of metrics to check for unwanted bias in datasets and machine learning models, and state-of …

Feb 25, 2025 · TDiMS : A Topological Distance based Intra-Molecular Substructure Descriptor for Improved Machine Learning Predictions for AAAI 2025 by Lisa Hamada et al.

Oct 12, 2021 · We see Neuro-symbolic AI as a pathway to achieve artificial general intelligence. By augmenting and combining the strengths of statistical AI, like machine learning, with the capabilities …

Mar 25, 2024 · Model reprogramming enables resource-efficient crossdomain machine learning by repurposing and reusing a welldeveloped pre-trained model from a source domain to solve tasks in a …

Aug 13, 2023 · Besides density functional theory and empirical force fields, machine learning has emerged as a novel and effective framework, leading to the family of so-called neural network …

Mar 3, 2024 · We benchmark a variety of machine learning models---linear regression, random forests, multi-layer perceptrons, and graph neural networks---on diverse classes of quantum circuits, over …