Deep Learning
A Mathematical Introduction
Welcome
Dear Faculty, Students and Learners
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Overview
Part-1: A Mathematical Introduction to Deep Learning Models
- Feed Forward Neural Networks (FFNs)
- Convolution Neural Networks (CNNs)
- Kolmogorov-Arnold Networks (KANs)
- Recurrent Neural Networks (RNNs)
- Transformers
- Graph Neural Networks (GNNs)
- Selective Structured State Space Models (S4)
Part-2: A Mathematical Introduction to Deep Generative Models
- Variational Auto Encoders (VAEs)
- Generative Adversarial Networks (GANs)
- Flow Networks
- Diffusion Models