Why is "Attention (machine learning)" trending?

Search Interest Perspective

• Machine learning global atomic representations with Euclidean fast attention - Nature
• Attention detection using EEG signals and machine learning: A review - EurekAlert!
• EEG-based characterization of auditory attention and meditation: an ERP and machine learning approach - Frontiers
• How Smooth Is Attention? - Apple Machine Learning Research
• What is self-attention? - IBM
• Mixture of Block Attention (MoBA), Microsoft’s Magma AI, Python Machine Learning by Example, Mistral Saba - Packt
• Attention in Psychology, Neuroscience, and Machine Learning - Frontiers
• Theory, Analysis, and Best Practices for Sigmoid Self-Attention - Apple Machine Learning Research
• Retinal fundus imaging as biomarker for ADHD using machine learning for screening and visual attention stratification - Nature
• Variable Attention Masking for Configurable Transformer Transducer Speech Recognition - Apple Machine Learning Research
• Using explainable machine learning and eye-tracking for diagnosing autism spectrum and developmental language disorders in social attention tasks - Frontiers
• Machine learning map of climate policy literature reveals disparities between scientific attention, policy density, and emissions - Nature
• Deploying Attention-Based Vision Transformers to Apple Neural Engine - Apple Machine Learning Research
• Impact of depressed state on attention and language processing during news broadcasts: EEG analysis and machine learning approach - Nature
• A Sequential Machine Learning-cum-Attention Mechanism for Effective Segmentation of Brain Tumor - Frontiers
• Apple Machine Learning Research at ICLR 2025 - Apple Machine Learning Research
• Using machine learning to simultaneously quantify multiple cognitive components of episodic memory - Nature
• Probabilistic Attention for Interactive Segmentation - Apple Machine Learning Research
• State Spaces Aren’t Enough: Machine Translation Needs Attention - Apple Machine Learning Research
• Stabilizing Transformer Training by Preventing Attention Entropy Collapse - Apple Machine Learning Research
• Machine-learning-based diagnosis of drug-naive adult patients with attention-deficit hyperactivity disorder using mismatch negativity - Nature
• Exploring the relationship between audio–visual perception in Fuzhou universities and college students' attention restoration quality using machine learning - Frontiers
• Performance prediction of sintered NdFeB magnet using multi-head attention regression models - Nature
• Pretraining of attention-based deep learning potential model for molecular simulation | npj Computational Materials - Nature
• A temporal stochastic bias correction using a machine learning attention model - Cambridge University Press & Assessment
• Fig. 16, [Divided space-time attention mechanism. Embedding...]. - Machine Learning for Brain Disorders - National Institutes of Health (.gov)
• Brain Reveals Attention Works Like a Zoom Lens - Neuroscience News
• Attention from Alignment, Practically Explained - Towards Data Science
• ‘It keeps me awake at night’: machine-learning pioneer on AI’s threat to humanity - Nature
• An Attention Free Transformer - Apple Machine Learning Research
• The Three Ages of Data Science: When to Use Traditional Machine Learning, Deep Learning, or a LLM (Explained with One Example) - Towards Data Science
• Assessment of embryotoxic effects of quinoline yellow using attention-based convolutional neural network and machine learning in zebrafish model - Frontiers
• Efficient Diffusion Models without Attention - Apple Machine Learning Research
• Developing attention deficits/hyperactivity disorder-virtual reality diagnostic tool with machine learning for children and adolescents - Frontiers
• A machine learning approach to risk based asset allocation in portfolio optimization - Nature
• How the State Department used AI and machine learning to revolutionize records management - FedScoop
• Enhancing Intelligent HVAC optimization with graph attention networks and stacking ensemble learning, a recommender system approach in Shenzhen Qianhai Smart Community - Nature
• Hands-On Attention Mechanism for Time Series Classification, with Python - Towards Data Science
• ELEGNT: Expressive and Functional Movement Design for Non-Anthropomorphic Robot - Apple Machine Learning Research
• Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach - Nature
• Accurate piezoelectric tensor prediction with equivariant attention tensor graph neural network - Nature
• Deploying Transformers on the Apple Neural Engine - Apple Machine Learning Research
• One Wide Feedforward is All You Need - Apple Machine Learning Research
• Integral Ad Science Ties Ad Results to Attention Measurement - Broadcasting + Cable
• Capsules with Inverted Dot-Product Attention Routing - Apple Machine Learning Research
• Integration of multimodal imaging data with machine learning for improved diagnosis and prognosis in neuroimaging - Frontiers
• Machine learning for clinical decision-making: pay attention to what you don’t see - statnews.com
• Time Series Forecasting with Deep Learning and Attention Mechanism - Towards Data Science
• A model for epileptic EEG detection and recognition based on Multi-Attention mechanism and Spatiotemporal - Nature
• Plastic Dinosaur plays ball. Machine learning attention loops… | by Michael Barnard | The Future is Electric - Medium
• Multi-task Learning with Cross Attention for Keyword Spotting - Apple Machine Learning Research
• Enhancing Paragraph Generation with a Latent Language Diffusion Model - Apple Machine Learning Research
• Training a machine learning classifier to identify ADHD based on real-world clinical data from medical records - Nature
• Data leakage inflates prediction performance in connectome-based machine learning models - Nature
• SimpleFold: Folding Proteins is Simpler than You Think - Apple Machine Learning Research
• Efficient Multi-view Stereo via Attention-Driven 2D Convolutions - Apple Machine Learning Research
• Predicting poor performance on cognitive tests among older adults using wearable device data and machine learning: a feasibility study - Nature
• Use of machine learning on clinical questionnaires data to support the diagnostic classification of Attention DeficitHyperactivity Disorder: a personalized medicine approach - Cambridge University Press & Assessment
• DeepETA: How Uber Predicts Arrival Times Using Deep Learning - Uber
• Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples | Translational Psychiatry - Nature
• Attention-based Deep Multiple Instance Learning - Towards Data Science
• What is GPT-3 and why is it so powerful? - Towards Data Science
• A Robust Machine Learning Based Framework for the Automated Detection of ADHD Using Pupillometric Biomarkers and Time Series Analysis - Nature
• The Uniqueness of Attention Affecting Corporate Growth: An Analysis of Annual Securities Reports Using Machine Learning - 慶應義塾
• Predicting scalar coupling constants by graph angle-attention neural network - Nature
• Adding an attention mechanism to RNNs - KDnuggets
• What is the future of machine learning? - TechTarget
• How machine learning and drones are helping prevent wildfires - About Amazon
• Finally a Book on Attention! - KDnuggets
• Machine learning helps predict ADHD in kindergarten students - University of Alberta
• Gradformer: A Machine Learning Method that Integrates Graph Transformers (GTs) with the Intrinsic Inductive Bias by Applying an Exponential Decay Mask to the Attention Matrix - MarkTechPost
• Highly accurate protein structure prediction with AlphaFold - Nature
• Box deepens partnership with Microsoft and turns its attention to AI and machine learning - TechCrunch
• Annealing-Based Attention: A Quantum Leap in AI Efficiency for Modern Deep Learning Models - Quantum Zeitgeist
• Applying Machine Learning to Kinematic and Eye Movement Features of a Movement Imitation Task to Predict Autism Diagnosis - Nature
• Google AI Research Introduces Titans: A New Machine Learning Architecture with Attention and a Meta in-Context Memory that Learns How to Memorize at Test Time - MarkTechPost
• Award-winning study: We have to realise that machine learning models cannot be trusted with absolute certainty - Helsinki.fi