Google DeepMind Researchers Propose Matryoshka Quantization: A Technique to Enhance Deep Learning Efficiency by Optimizing Multi-Precision Models without Sacrificing Accuracy  MarkTechPostRead More

Physics-informed Bayesian optimization suitable for extrapolation of materials growth  Nature.comRead More

Future to be dramatic with new advances expected in AI: Prez  The Tribune IndiaRead More

Stress hyperglycemia ratio and machine learning model for prediction of all-cause mortality in patients undergoing cardiac surgery  Cardiovascular DiabetologyRead More

Self-supervised identification and elimination of harmful datasets in distributed machine learning for medical image analysis  Nature.comRead More

Jeff Dean’s Insights on Large Scale Machine Learning for Public Health  Blockchain.NewsRead More

Exploration of contemporary modernization in UWSNs in the context of localization including opportunities for future research in machine learning and deep learning  Nature.comRead More

Google DeepMind Researchers Propose Matryoshka Quantization: A Technique to Enhance Deep Learning Efficiency by Optimizing Multi-Precision Models without Sacrificing Accuracy  MarkTechPostRead More

Utilization of machine learning algorithm in the prediction of rehospitalization during one-year post traumatic spinal cord injury  Nature.comRead More

An explainable and accurate transformer-based deep learning model for wheeze classification utilizing real-world pediatric data  Nature.comRead More