TrAC Student Journal Club – Timilehin Ayanlade
Title: Unified Training of Universal Time Series Forecasting Transformers
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TrAC Seminar Series – Seyed Vahid Mirnezami
Title: Transforming AI Practices: From Data Generation to Automated MLOps Abstract Agility enables swift adaptation to changing market needs and new technologies. Moreover, mature AI utilization necessitates a strategic shift, focusing on incorporating AI into core business operations to boost efficiency and drive innovation. Increasing agility and harnessing the power of mature AI, this presentation […]
ADLRG – Federated Learning – 2
TrAC ADLRG Mini-course on Federated Learning (class 2/3) In this mini-course, we will cover concepts in Federated Learning.
TrAC Seminar Series – Jinlong Wu
Title: Operator learning for data-driven closure models of complex dynamical systems Abstract Closure models are widely used in simulating complex multiscale dynamical systems such as turbulence and Earth’s climate, for which direct numerical simulation that resolves all scales is often too expensive. For those systems without a clear scale separation, deterministic and local closure models […]
ADLRG – Federated Learning – 3
TrAC ADLRG Mini-course on Federated Learning (class 3/3) In this mini-course, we will cover concepts in Federated Learning.
Deep Dive into AI
Welcome to the TrAC Bootcamp on "Deep Dive into AI" Get ready for a hands-on, four-day journey into the world of Artificial Intelligence at our upcoming TrAC Bootcamp. Whether you're […]
TrAC Advanced AI Course on Scientific Machine Learning
Course Description Dive into the theory, implementation, and limitations of Scientific Machine Learning (SciML) models. In this course, you will engage in hands-on and practical activities under the expert guidance […]
$500
TrAC Foundational AI Course on MLOps
Join our dynamic MLOps course and discover how machine learning has been transformed from a research tool into a key component of modern applications used by millions. In this hands-on […]
$500
TrAC Seminar Series – Ping Guo
Detail Date: September 18, 2024 Time: 11:00 AM - 12:00 PM CST Location: https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Deep learning enabled computer vision metrology: from strain estimation to form measurement Abstract The embryo of Industry 4.0 has been transforming manufacturing into an autonomous, adaptive, and responsive paradigm while setting a higher standard for efficiency, accuracy, and reliability. These […]
TrAC Seminar Series – Qi An
Detail Date: October 9, 2024 Time: 11:00 am - 12:00 pm CST Location: 2004 Black Engineering or https://iastate.zoom.us/j/95263587232?pwd=K1BVcURvWExFb3pUT000NlRwdFZsZz09 Title: Understanding Reaction Mechanisms of Ammonia Synthesis through the Combination of Deep Reinforcement Learning and Density Functional Theory Abstract The Haber–Bosch (HB) process is the foundation of industrial ammonia (NH₃) production, essential for manufacturing nitrate-based fertilizers and […]