Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

Explore how AI predictive analytics reshapes industries by providing insights, forecasting trends, and enhancing ...

Techniques such as Raman spectroscopy, Fourier-transform infrared (FTIR) spectroscopy, nuclear magnetic resonance (NMR), and near-infrared (NIR) spectroscopy provide detailed biochemical fingerprints ...

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...

Weather forecasting is not easy. The truth is that predicting future weather conditions over broad, or even narrow, swaths of Earth's surface comes down to complex microphysical processes, and as ...

KAIST (President Kwang Hyung Lee) announced on the 20th that a research team led by Professor Sungjin Ahn in the School of Computing has developed a ...

As demand for uninterrupted power delivery intensifies, utilities are adopting advanced vegetation management techniques to ...

Structured maturity models can address program, reliability and safety improvements while ensuring regulatory compliance.

We want to be able to better predict storms over Connecticut and the Northeast US, which is why we started this exploration with ...

Diffusion models are widely used in many AI applications, but research on efficient inference-time scalability, particularly for reasoning and planning (known as System 2 abilities) has been lacking.