The whitepaper represents the first-ever analysis of the impact of stochastics effects from the perspective of resolution. A gap has emerged between the size of features that can be patterned in ...

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 ...

We propose a Crystal Diffusion Variational Autoencoder (CDVAE) that captures the physical inductive bias of material stability. By learning from the data distribution of stable materials, the decoder ...

In recent years, autoencoders and their variants have emerged as effective tools for hyperspectral anomaly detection. Nevertheless, owing to the complex distribution of anomalous regions and the ...

Process shift of multimode process involving data distribution and dynamic relation makes traditional transfer learning methods be intractable and even result in negative transfer. To tackle this ...