Tag: transformers

A new survey in Artificial Intelligence Review provides the first comprehensive map of language modeling for tabular data, tracing the ...

A systematic review maps how deep learning architectures are transforming EEG analysis for neurological disease diagnosis, while warning that data ...

Researchers built ViTDrone, a Vision Transformer framework that simultaneously steers a drone through corridors and detects collisions while using Grad-CAM ...

A max-plus neural architecture aligns deep learning with the polyhedral structure of phylogenetic tree space, cutting distance-matrix error by more ...

A new review shows that hybrid deep learning and swarm-optimized AI models are achieving near-perfect prediction of lithium-ion battery charge, ...

A new systematic review and meta-analysis of 23 studies finds that machine learning models for peptide–target interaction prediction achieve strong ...

Researchers have integrated transformer attention mechanisms into learned primal-dual PET reconstruction, achieving cleaner images from noisy low-count scanner data.

The CMS Collaboration has demonstrated the first machine-learning-based full-event reconstruction applied to hadron collider data, achieving better jet energy resolution ...

A new convolutional architecture called MRTFNet combines multi-resolution temporal embeddings with frequency-domain modeling to outperform Transformer-based models on most long-term ...

Researchers show that temporally correlated input noise, not model capacity, drives unstable long-horizon forecasts, and introduce NoDE, a lightweight embedding ...