Neural networks allow programs to recognize patterns and solve common problems in artificial intelligence, machine learning and deep learning.
Digital Journal: The pen that reshaped deep learning: A bold take on neural networks
In recent years, as the field of deep learning has matured, a small but growing group of researchers and technologists has begun to question the prevailing assumptions behind neural networks. Among ...
The pen that reshaped deep learning: A bold take on neural networks
Booth School of Business: Paper Deep Neural Networks for Estimation and Inference
We study deep neural networks and their use in semiparametric inference. We establish novel rates of convergence for deep feedforward neural nets. Our new rates are sufficiently fast (in some cases ...
Medical Xpress: Neural biomarkers identified for obsessive-compulsive disorder symptoms in deep brain networks
For the first time, researchers at the Netherlands Institute for Neuroscience and Amsterdam UMC have identified what happens in neural networks deep within the brain during obsessive thoughts and ...
EurekAlert!: Revolutionizing fragrance design using deep neural networks (DNNs) scent profiles from chemical data
Revolutionizing fragrance design using deep neural networks (DNNs) scent profiles from chemical data
Neural networks are machine learning models that mimic the complex functions of the human brain. These models consist of interconnected nodes or neurons that process data, learn patterns and enable tasks such as pattern recognition and decision-making.
MSN: AI neural fields enable clearer deep brain imaging without extra hardware
Researchers from KAIST and UC Berkeley have developed a neural network-based method to correct optical distortions in deep tissue microscopy without additional hardware. The system uses Neural Fields ...