Neural network model can improve understanding of human attention
Imagine watching a speaker and another person nearby is loudly crunching from a bag of chips. To deal with this, a person ...
Machine learning sheds light on how the human brain perceives feeling
How the brain feels about the world around it is the subject of a new paper published in Proceedings of the National Academy ...
Science Daily11h
A geometric deep learning method for decoding brain dynamics
Scientists have developed a geometric deep learning method that can create a coherent picture of neuronal population activity during cognitive and motor tasks across experimental subjects and ...
Semiconductor Engineering13h
HW-Aligned Sparse Attention Architecture For Efficient Long-Context Modeling (DeepSeek et al.)
Hardware-Aligned and Natively Trainable Sparse Attention” was published by DeepSeek, Peking University and University of Washington. Abstract “Long-context modeling is crucial for next-generation ...
Impacts6d
The Next Frontier: Advancements in Multimodal AI Systems
In this digital era, artificial intelligence continues to push boundaries, with multimodal AI representing a transformative ...
C&EN16d
HiRXN: Hierarchical Attention-Based Representation Learning for Chemical Reaction
Find more information about Crossref citation counts. The Altmetric Attention Score is a quantitative measure of the attention that a research article has received online. Clicking on the donut icon ...
IEEE21d
Enhancing medical vision-language contrastive learning via inter-matching relation modelling
Abstract: Medical image representations can be learned through medical vision-language contrastive learning (mVLCL ... of-the-art mVLCL methods with consistent improvements across single-modal and ...
IEEE23d
Deep Reversible Consistency Learning for Cross-modal Retrieval
Abstract: Cross-modal retrieval (CMR) typically involves learning common representations to directly measure similarities between multimodal samples. Most existing CMR methods commonly assume ...
Frontiers26d
Graph Convolutional Networks for multi-modal robotic martial arts leg pose recognition
PoseGCN leverages spatial-temporal graph encoding to capture joint motion dynamics, an action-specific attention ... a self-supervised learning module to pre-train the model with unlabeled data so ...
C&EN27d
Machine Learning-Based Multi-Modal and Multi-Granularity Feature Fusion Framework for Accurate Prediction of Molecular Properties
Key Laboratory of Smart Manufacturing in Energy Chemical Process, East China University of Science and Technology, Ministry of Education, Shanghai 200237, China ...
The Atlantic28d
You’re Being Alienated From Your Own Attention
Every single aspect of human life across the broadest categories of human organization is being reoriented around the pursuit of attention. It is now the defining resource of our age. The ...