Physics-Informed AI Tackles Drought Forecasting in a Stressed Transboundary Basin
A new study tests a Transformer-based physics-informed neural network against support vector regression for forecasting hydrological drought in the transboundary ...
A new study tests a Transformer-based physics-informed neural network against support vector regression for forecasting hydrological drought in the transboundary ...
A new confidentiality-preserving spiking neural transformer detects breast cancer in histopathology images with over 98% accuracy while computing entirely on ...
A new deep learning framework called Epiformer combines the Evo 2 genome language model with a dual-channel network to detect ...
Researchers in Beijing have built a 0.27-megabyte transformer model that detects multi-stage APT attacks in industrial IoT telemetry with high ...
A transformer-based machine learning model can detect and even predict diffuse cerebral edema in cardiac arrest survivors from routine EEG ...
Researchers have developed a personalized N-of-1 transformer framework that learns an individual's daily behavior patterns from smart home activity logs ...
Researchers used a deep learning model to compress 38 senescence-linked blood proteins into a single SASP Score that predicts mortality, ...
A new parallel deep learning framework combining CNN and Transformer branches with thermodynamic regularization improves the prediction of mutation-induced protein ...
Researchers in China have developed a Multimodal Transformer Attention model that jointly extracts and fuses video, audio and text features ...
Researchers have developed ADLM-TiM, a hybrid deep learning and Transformer model that detects advanced persistent threats in highly imbalanced network ...
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© 2025 Scienmag - Science Magazine