Enfow's Blog
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📚 Posts
Computer-Science
[OS]
from Batch processing to Time sharing
[OS]
Kernel and System call
[OS]
Monolithic kernel and MicroKernel
[OS]
What is Process
[OS]
Interprocess Communication
[OS]
CPU Scheduling
[OS]
Thread
[OS]
Multi Process & Multi Thread
[IP]
Routing Protocol BGP & OSPF
[IP]
ICMP Internet Control Message Protocol
[IP]
Transport Layer Protocols, TCP & UDP
[Programming]
Asymptotic Notation
[Programming]
Functional Programming and Static Type Checking With Ocaml
[Programming]
Keywords for OOP
Python
Python Bulit-in Time Complexity: List
Python Bulit-in Time Complexity: Set & Dictionary
Python import system
Python Global Interpreter Lock
Python String Formatting
% operator, format(), f'string'
Deep-Learning
Gradient Descent
Convolution Neural Network
Loss function and Maximum likelihood
Energy Based Model
Reinforcement-Learning-Introduction
Multi-armed Bandit
Markov Property and Bellman Equation
Dynamic Programming
Monte Carlo Methods
Temporal Difference
Planning and Learning
On-Policy Approximation of Action Values
Policy Gradient Method
Bellman Operator
Statistics
Expectation, Variance and Covariance
Probability Distributions
Bayesian Rule
Decision Theory
Shannon Entropy
MLE / MAP
ROC Curve
Linear-Algebra
Quick Review: Linear Algebra
Linear Algebra Introduction
Linear Combination
Linear Mapping
Inner Product and Norm
Least Square Problem
Orthogonality
EigenDecomposition
Singular Value Decomposition
Outper Product and Determinant
Optimization
[Optimization]
Optimization Problem
[ConvexOptimization]
Convex Optimization Introduction
Mathematics-for-ML
Taylor Series
Differentiation of Multivariate Function
Experiments
[DL]
Universal Approximation Experiment
Neural-Network Papers
[Universal Approximation]
Approximation by Superposition of a Sigmoidal Function
[Optimizer]
An overview of gradient descent optimization algorithms
[Activation]
Smooth Adversarial Training
[Batch Normalization]
Accelerating Deep Network Training by Reducing Internal Covariate Shift
Generative-Model Papers
[VAE]
Auto-Encoding Variational Bayes
[GAN]
Generative Adversarial Nets
[AAE]
Adversarial AutoEncoders
Model-Free-RL Papers
[DQN]
Playing Atari with Deep Reinforcement Learning
[DDQN]
Deep Reinforcement Learning with Double Q-learning
[Dueling DQN]
Dueling Network Architectures for Deep Reinforcement Learning
[DPG]
Deterministic Policy Gradient Algorithms
[DDPG]
Continuous Control with Deep Reinforcement Learning
[TD3]
Addressing Function Approximation Error in Actor-Critic Methods
[SAC]
Off-Policy Maximum Entropy Deep Reinforcement Learning with a Stochastic Actor
[OAC]
Better Exploration with Optimistic Actor-Critic
[TRPO]
Trust Region Policy Optimization
[PER]
Prioritized Experience Replay
[HER]
Hindsight Experience Replay
Model-Based-RL Papers
[DeepDyna Q]
Integrating Planning for Task-Completion Dialogue Policy Learning
[WorldModel]
World Models
[PlaNet]
Learning Latent Dynamics for Planning from Pixels
[Dreamer]
Dream to Control: Learning Behaviors by Latent Imagination
Parallel-RL Papers
[A3C]
Asynchronous Methods for Deep Reinforcement Learning
[IMPALA]
Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
Multi-Agent-RL Papers
[COMA]
Counterfactual Multi-Agent Policy Gradients
Batch-RL Papers
[BCQ]
Off-Policy Deep Reinforcement Learning without Exploration
[REM]
Striving for Simplicity in Off-Policy Deep Reinforcement Learning
Distributional-RL Papers
[C51]
A Distributional Perspective on Reinforcement Learning
Meta-Learning Papers
[Matching Network]
Matching Networks for One Shot Learning
[MAML]
Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
Sequence-to-Sequence Papers
[RNN Encoder-Decoder]
Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
[Attention]
Neural Machine Translation by Jointly Learning to Align and Translate
Large-Language-Model Papers
OpenAI o1
[GPT-1]
Improving Language Understanding by Generative Pre-Training
[BERT]
Pre-training of Deep Bidirectional Transformers for Language Understanding
[GPT-2]
Language Models are Unsupervised Multitask Learners
[GPT-3]
Language Models are Few-Shot Learners
[Instruct GPT]
Training language models to follow instructions with human feedback
[Chain-of-Thought]
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
[Dialogue-generation]
Large Language Models meet harry potter
Transfer-Learning Papers
[Transfer Learning]
Learning and Transferring Mid-Level Image Representations using Convolutional Neural Networks
Graph-Neural-Network Papers
Relational Inductive Biases, Deep Learning, and Graph Networks
[GCN]
Semi-Supervised Classification with Graph Convolutional Networks
[LGCN]
Large-Scale Learnable Graph Convolutional Networks
Combinatorial-Optimization Papers
[Placement]
Device Placement Optimization with Reinforcement Learning
[Placement]
Chip Placement with Deep Reinforcement Learning
[NP-hard graph]
Learning Combinatorial Optimization Algorithms over Graphs
Anomaly-Detection Papers
Variational AutoEncoder based Anomaly Detection using Reconstruction Probability
Segmentation Papers
[FCN]
Fully Convolutional Networks for Semantic Segmentation
[3D Segmentation]
Deep Neural Networks for Anatomical Brain Segmentation
Semiconductor
[FPGA]
Field Programmable Gate Array
[Placement]
VLSI Cell Placement Technique
Robotics
[Industrial Robot]
Balancing a Robotic Spot Welding Manufacturing Line: an Industrial Case Study
Machine-Learning-project
[Python]
Pandas, Pytorch
[RL]
Install Mujoco Environment
[RL]
Mujoco Env: Reacher & Hopper
[RL]
Gym Documentation
[MlFlow]
mlflow Introduction
Environment-Settings
[Python]
pyenv, virtualenv, autoenv
[Vim]
Customizing Vim
[Git]
Github SSH Setting
[Git]
Git Pre-Commit Settings
[Tools]
Linting & Formatting
[Linux]
Linux Remote Server Settings
[Docker]
Docker Introduction
Embedded
[RaspberryPi]
Raspberry Pi initial Setup
Install Ubuntu & Connect WiFi
[RaspberryPi]
Raspberry Pi GPIO Control
Survo Moter Control With Raspberry Pi
