This tutorial discusses the challenges and opportunities of using modern AI for inverse problems and scientific applications more broadly. In particular I will discuss an emerging literature on deep learning for inverse problems that have been very successful for a variety of image and signal recovery and restoration tasks ranging from denoising and MR reconstruction … Continue reading Tutorial on Modern AI for Inverse Problems
Transformer architectures have risen as the preferred choice among deep-learning models, finding applications in diverse fields such as natural language processing, computer vision, and time-series forecasting. Notably, it forms the core of large language models like ChatGPT. What sets Transformers apart from conventional models like fully connected networks (FCNs), convolutional neural networks (CNNs), and residual … Continue reading ICASSP 2024 Tutorial on Fundamentals of Transformers
Ever wonder what allows the AI you use to work so efficiently? Or how computers can process data and spit it back to you so quickly? In this age of digital and technological renaissance, machine learning models, AI technologies and quantum computing, humanity has transformed the way we interact with computational models. One of these … Continue reading Faculty affiliated with the AIF4S center receive $700,000 Air Force Grant for GPU Cluster
