This repository contains my homework submissions for the "Deep Generative Models" course offered at the University of Tehran in Fall 2023. The course was instructed by Dr. Tavassolipour and Dr. Sadeghi. The assignments cover a range of topics in deep generative modeling, including probabilistic graphical models, variational autoencoders, generative adversarial networks, and more.
Topics Covered:
- Probabilistic Graphical Model
- Causality
- Variational Inference
Topics Covered:
- Variational Auto Encoder (VAE)
- Normalizing Flow
Topics Covered:
- Generative Adversarial Networks (GAN)
- Diffusion Models
Topics Covered:
- Fine-tuning Large Language Models (LLM) using LoRA PEFT
- Prompt Engineering
- SpeechT5 Text-to-Speech (TTS) Fine-tuning
Special thanks to Dr. Tavassolipour and Dr. Sadeghi for their guidance and instruction throughout the course.