Lu, Yukuan

Sources:

1. Emerging Properties in Self-Supervised Vision Transformers (DINO)
2. PyTorch implementation and pretrained models for DINO

Sources:

1. ECS201A Homepage
2. ECS201A Projects(gem5)

All the experiments rely on the same python env and a software called gem5.

The professor has offered us github codespaces, such as classroom assignment-0, to develop,upon which you don't need to worry about the setup. So it's strongly recommended to develop with github codespaces.

However, if you prefer to develop on your local machine, to set up for the experiments you must:

1. Install and config gem5 on your system.
2. Clone the assignment repo and config it.

Sources:

1. --> How To Install Rust on Ubuntu 20.04

Sources:

1. How To Install Node.js on Ubuntu 20.04

Sources:

1. NvChad
2. NvChad --- Rocky Linux
3. Dreams of Code's NvChad playlist
4. BrunoKrugel's Github repo

Note: This article will only focus on NvChad itself. If you want to simply copy my computer configs (ALL OF THEM), you can refer to How to Set Up on A New Machine.

How to set up configs on a brand new machine (typically a ubuntu server).

For the usage of most of the rust tools, see my Unix CLI Tools.

My dotfiles are save in:

1

https://github.com/LYK-love/dotfiles-for-servers

1. Shiyu Zhao. Chapter 4: Value Iteration and Policy Iteration. Mathematical Foundations of Reinforcement Learning.
2. --> Youtube: Value Iteration and Policy Iteration

This chapter introduces three algorithms that are closely related to each other. Briefly speaking, they are all solutions of Bellman optimality equations (BOEs) to get optimal policies.

1. Shiyu Zhao. Chapter 3: Bellman Optimality Equation. Mathematical Foundations of Reinforcement Learning.
2. --> Youtube: Bellman Optimality Equation
3. --> Youtube: How to Solve Bellman Optimality Equation

The previous chapter introduced the Bellman equation of any given policy. The present post introduces the Bellman optimality equation, which is a special Bellman equation whose corresponding policy is optimal. By solving

Sources:

1. Shiyu Zhao. Chapter 2: State Values and Bellman Equation. Mathematical Foundations of Reinforcement Learning.
2. --> Youtube: Bellman Equation: Action Value

Sources:

• Masked Autoencoders (MAE)
• Vision Transformer (ViT)
• Segment Anything blog
• Github: SAM
• Youtube video: Segment Anything - Model explanation with code
  • -->Slides