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A Deep Dive into Deep Learning: Architectures and Algorithms
May 18, 2022 @ 9:00 am - 4:00 pm
The TrAC @ Iowa State University along with Midwest Big Data Summer School and CyVerse.org will host a day long workshop on Deep Learning Architectures and Algorithms.
Abstract
In this tutorial, we will be covering the theory and practical implementation of modern deep learning algorithms. We divide the tutorial into two sessions. The first session covers the building blocks of neural networks such as back-propagation and optimization algorithms and some hands-on supervised deep learning coding. The second session will be to dive deep into the nuts and bolts of Deep Learning, and more modern architectures such as ResNets, Transformers etc. and algorithms such Generative Adversarial Networks, Reinforcement Learning etc. We will finally conclude with some emerging topics in deep learning.
Agenda
All times shown in Central Daylight Time
| Time | Concept | Notes |
|---|---|---|
| 09:00 | Intro to Deep Learning (backpropagation, SGD and other concepts) | TBD |
| 10:00 | Convolutional Neural Networks – Architectures for Object Recognition | TBD |
| 10:55 | Short Break | |
| 11:00 | Convolutional Neural Networks – Architectures of Object Detection, Semantic Segmentation, Autoencoders, etc. | TBD |
| 12:00 | Lunch Break | |
| 13:30 | More architectures – LSTMs, Transformers, etc. | |
| 14:30 | Algorithms – Generative Adversarial Networks | |
| 14:55 | Short Break | |
| 15:00 | Algorithms – Reinforcement Learning | |
| 15:30 | Algorithms – Scientific Machine Learning | |
| 16:00 | Emerging topics in deep learning: Interpretability, adversarial learning, distributed deep learning etc. |
About Instructor
Aditya Balu is currently a Data Scientist at the Translational AI Center at Iowa State University, where he is working on generative designs physics-aware deep learning methodologies. He finished his Ph.D. at Iowa State University on Deep Learning and GPU computing for Design and Manufacturing before this. During his graduate studies, he also interned at ANSYS Inc., where he contributed to Deep Learning-based Topology Optimization. Before his graduate studies, he has also worked at an Oil & Gas industry, FMC Technologies (now known as Technip FMC), as a product design engineer where he was designing connectors and manifolds for subsea high pressure and high-temperature applications.
Tutorial Website
All the materials regarding the tutorial are posted here: https://translationalaicenterisu.github.io/deepdive2022/