MIT researchers unveil a new fine-tuning method that lets enterprises consolidate their "model zoos" into a single, ...

Traditional computational electromagnetics (CEM) methods—such as MoM, FEM, or FDTD—offer high fidelity, but struggle to scale ...

A machine learning model incorporating functional assessments predicts one-year mortality in older patients with HF and improves risk stratification beyond established scores. Functional status at ...

CNN in deep learning is a special type of neural network that can understand images and visual information. It works just like human vision: first it detects edges, lines and then recognizes faces and ...

Abstract: Deep learning has boosted fast in the last few years. This becomes an obstacle for numerous people to efficiently make use of these assets. The complexity of complicated architecture depends ...

Researchers at Nvidia have developed a new technique that flips the script on how large language models (LLMs) learn to reason. The method, called reinforcement learning pre-training (RLP), integrates ...

Abstract: The paper discusses how we can leverage cloud infrastructure for efficient hyperparameter tuning of deep neural networks on high dimensional hyperparameter spaces using Bayesian Optimization ...