-
DLRG – MLOps – 1
DLRG – MLOps – 1
TrAC DLRG Mini-course on MLOps (class 1/3) In this mini-course, we will cover DevOps and best practices for training, monitoring, and deploying deep learning models.
Loading view.
Calendar of Events
S Sun
M Mon
T Tue
W Wed
T Thu
F Fri
S Sat
0 events,
0 events,
1 event,
1 event,
-
Inaugural TrAC Day
Inaugural TrAC Day
Welcome to TrAC Day! Hosted by The Translational AI Center When: Wednesday, April 3rdTime: 3:00 p.m.Where: Student Innovation Center, Iowa State University About TrAC Day The Translational AI Center is thrilled to announce our inaugural TrAC Day, a pioneering event that celebrates the intersection of artificial intelligence, research, and industry collaboration. What to Expect Join […]
1 event,
-
ADLRG – Generative AI (vision) – 3
ADLRG – Generative AI (vision) – 3
TrAC ADLRG Mini-course on Generative AI (class 3/4) In this mini-course, we will cover concepts in Generative AI such as Diffusion, etc.
1 event,
-
TrAC Student Journal Club – Dhruv Gamdha
TrAC Student Journal Club – Dhruv Gamdha
Title: ∇-Prox: Differentiable Proximal Algorithm Modeling for Large-Scale Optimization Link to the paper: https://light.princeton.edu/publication/delta_prox/
0 events,
0 events,
0 events,
1 event,
-
DLRG – MLOps – 2
DLRG – MLOps – 2
TrAC DLRG Mini-course on MLOps (class 2/3) In this mini-course, we will cover DevOps and best practices for training, monitoring, and deploying deep learning models.
1 event,
-
TrAC Seminar Series – George Biros
TrAC Seminar Series – George Biros
Title: A Graph Neural Network Surrogate for Epitaxial Crystal Growth Abstract Predicting grain (crystal) formation and growth during alloy solidification is of great importance in additive manufacturing (AM) as it one of the key factors in determining the final microstructure and the mechanical properties of the printed part. Numerical simulations of grain formation involve moving […]
1 event,
-
ADLRG – Generative AI (vision) – 4
ADLRG – Generative AI (vision) – 4
TrAC ADLRG Mini-course on Generative AI (class 4/4) In this mini-course, we will cover concepts in Generative AI such as Diffusion, etc.
1 event,
0 events,
0 events,
0 events,
1 event,
-
DLRG – MLOps – 3
DLRG – MLOps – 3
TrAC DLRG Mini-course on MLOps (class 3/3) In this mini-course, we will cover DevOps and best practices for training, monitoring, and deploying deep learning models.
1 event,
-
TrAC Seminar Series – Iro Armeni
TrAC Seminar Series – Iro Armeni
Title: Living Scenes:Â Creating and updating digital twins of evolving indoor scenes Abstract Buildings are like living organisms, i.e., they evolve over time due to interaction with natural phenomena and humans. […]
1 event,
-
Federated Learning – 1
Federated Learning – 1
TrAC ADLRG Mini-course on Federated Learning (class 1/3) In this mini-course, we will cover concepts in Federated Learning.
2 events,
-
TrAC Student Journal Club – Timilehin Ayanlade
TrAC Student Journal Club – Timilehin Ayanlade
Title: Unified Training of Universal Time Series Forecasting Transformers
0 events,
0 events,
0 events,
0 events,
1 event,
-
TrAC Seminar Series – Seyed Vahid Mirnezami
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, […]
1 event,
-
ADLRG – Federated Learning – 2
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.
0 events,
0 events,
0 events,
0 events,
0 events,
1 event,
-
TrAC Seminar Series – Jinlong Wu
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 […]
1 event,
-
ADLRG – Federated Learning – 3
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.