The Stanford team’s deep-learning algorithm, called UrbanDenoiser, has been trained on data sets of 80,000 samples of urban seismic noise and 33,751 samples that indicate earthquake activity.

Here we report a deep reinforcement learning approach based on AlphaZero1for discovering efficient and provably correct algorithms for the multiplication of arbitrary matrices. Our agent, AlphaTensor, ...

Algorithms and deep learning: the best of both worlds. Veličković was in many ways the person who kickstarted the algorithmic reasoning direction in DeepMind.

Deep Learning Pioneer Geoffrey Hinton Publishes New Deep Learning Algorithm This item in japanese Jan 10, 2023 2 min read by. Anthony Alford. Write for InfoQ Feed your curiosity. ...

Deep learning algorithms allow computers to learn from large amounts of data and are known for advancing the state of the art in the artificial intelligence field, leading to smarter cancer treatments ...

Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study. The Lancet Digital Health , 2022; 4 (9): e657 DOI: 10.1016/S2589 ...

Deep learning, a subset of machine learning, refers to machine learning that takes place on artificial intelligence neural networks. Written by eWEEK content and product recommendations are ...

Automated methods enable the analysis of PET/CT scans (left) to accurately predict tumor location and size (right). Credit: Nature Machine Intelligence (2024). DOI: 10.1038/s42256-024-00912-9 ...

Deploying deep learning algorithms on embedded platforms involves a structured process that optimizes models, considers hardware constraints, and addresses real-time performance requirements. By ...

Commentary: We’ve been overhyping deep learning for too long. It’s time to start embracing it as a complement to, not replacement for, human ingenuity.