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RNN

12-21

Poincare Conjecture/Theorem and Ricci Flow

12-21

Block

12-25

Lorem ipsum dolor sit amet, consectetur adipiscing elit. Aliquam justo turpis, tincidunt ac convallis id.

12-24

Categories

12-24

Link Post

12-24

Tags

12-24

Elements

12-24

Categories

12-24

Categories

12-24

中文測試

12-24

MathJax with Jekyll

02-16

Gallery Post

11-18

Highlight Test

07-19

Next Theme Tutorial

07-20

Graph RAG

07-28

MMLU Dataset and Performance

06-29

HuggingFace LLM

06-29

MMLU and MMLU Pro

06-21

MMLU on GPT

06-18

Ollama Llama3

06-16

Token Economy

06-15

Big Little LLMs Applications

06-13

Token and Embedding (詞元和嵌入)

06-10

World Model Comparison 世界模型技術路綫

06-02

Acceptance-Rejection Sampling 接受拒絕採樣

05-26

Equal Distribution - 什麽是機率分佈相等？

05-26

End-to-end 端到端模型

05-25

AI Agent 實例

05-12

Why does diffusion work better than auto-regression?

05-07

大(語言)模型參數微調 PEFT

05-07

中文亂碼二分之一

05-03

文本分類 - IMDB 意見分析

05-01

大語言和自然語言處理的差異

05-01

中文編碼，亂碼，轉碼

04-21

Hyena Vs. Transformer

04-12

Trans-tokenizer

04-08

HuggingFace Dataset and Pytorch Dataset I

04-03

HuggingFace Dataset and Pytorch Dataset I

04-03

Colab 使用方法

03-24

AI Coding 編程

03-23

HuggingFace Tokenizer Function

03-20

Physics Informed ML/AI

03-03

LLM Tokenizer Code

02-21

VS Code for Jupyter

02-12

AI Markdown Editor

02-04

Work

02-01

Mamba Vs. Transformer

01-28

Whisper Fine Tune

01-20

Long Mistral

01-09

簡單文本編輯器

01-06

Streaming LLM

01-04

LLM Performance Benchmark

12-24

Llama Quantization

12-23

RAG + Long Context

12-22

Perplexity of LLM

12-19

LLM KV Cache Code

12-16

Autoregressive Math Model

12-12

LLM - Medusa on GPU with Limited Memory

12-10

VS Code for WSL2

12-09

LLM 性能分析

12-09

Speculative Decode

12-04

LLM Lookahead Decode

12-04

LLM Tokenizer

12-02

Retrieval Augmented Generation - RAG

11-29

Llama on CPU using CPP

11-26

Attention As Graph

11-25

LLM Agent

11-12

LLM Prune

11-12

LLM 計算量分析

11-04

LLM KV Cache Memory and BW

10-29

LLM 記憶體分析

10-21

LLM Toy Example

10-14

Long Context

10-14

LLM App - Lang Chain

06-24

Flash Attention

06-20

MLP Is All You Need

04-09

Convolution Is All You Need

04-09

Attention Is All You Need

04-09

RLHF

04-09

Paper Study By Amazon Li Mu and Zhu

04-08

Matrix Multiplication and Tensor Decomposition (?)

04-04

推薦系統初探 Recommendation System Exploration

04-01

LLM 三部曲 Part I Foundation Model

03-26

Semantic Search Using Query-Key Similarity

03-22

Generative AI Fine Tune

03-22

Generative AI Fine Tune

03-22

Generative AI Fine Tune

03-22

Semantic Search Query-Key-Value

03-22

Token and Embedding, Query-Key-Value

03-19

Mixed Language Output

03-05

Prompt for LLM

03-05

Next Word Prediction Us GPT

02-26

HuggingFace Transformer

02-26

Nano GPT

02-20

Self Attention of GPT

02-18

Generative AI- Stable Diffusion

02-07

Generative AI- Stable Diffusion

02-07

Deep Learning using Nonequilibrium Thermodynamics

02-07

Graph Matrix Representation Applications

01-30

二次式和正定矩陣 Quadratic Form and Positive Definite Matrix

01-28

Graph and Eigenvalue

01-28

WSL Command

11-07

如何避免 Softmax overflow or underflow

11-07

Python Project Management - Testing

10-22

如何避免 normalized L2-norm or layer norm FP16 overflow or underflow

10-09

Transformer for Speech Recognition

03-21

Vision Transformer

02-27

VScode for Python and Julia

02-05

Parser From Scratch

02-01

Neural Network and CV Optical Flow 算法

01-05

Computer Vision My Way

12-18

Improve Engineer Efficiency - Python Image Library

12-11

跨平臺 Markdown Plus MathJax Blog Editing 分享

09-12

Jekyll Memo for Github Blog

06-30

增進工程師效率 Python DataFrame - CSV & Plot

12-21

Edge AI

08-09

Hybrid AI

08-08

LLM 趨勢

08-03

RAG vs. Long Context vs. Fine-tuning

07-29

Math AI - 演繹推理和可信推理

07-24

Less is More, But Scale Matters

07-24

Math AI - 機率論或論機率？

07-19

Curse or Bless of Dimensionality

07-18

Makemore Karpathy

02-20

ML Normalization

02-14

AI for AI (II) - Jupyter-ai

02-07

LLM MoE Toy Example

02-06

Web Crawler or Scraper

10-16

Dynamic Data Crawler

10-14

Static Data Crawler

10-01

Math Stat II - XYZ Entropy and XYZ Information

09-24

AI for AI (I) - Github Copilot

09-24

Julia Code Snip

09-20

Graph Machine Learning - Laplacian Operator

08-27

GNN - Graph Laplacian Operator/Matrix

08-27

Windows + ML CUDA - Anaconda / WSL2 / DirectML

08-13

vSLAM with NN

05-13

vSLAM with NN

05-13

vSLAM with NN

05-13

CV-SLAM Bundle Adjustment (BA)

04-23

Human Brain

04-23

CV-SLAM Feature Extraction - SIFT/SURF/ORB

04-16

vSLAM Introduction

04-15

A Unified View of Self-Supervised Learning (SSL)

04-05

AI Hand Pose and Tracking

04-01

SLAM Demystify

03-25

Thermal Resistance

01-17

Math AI Flow and Flux PDE

01-16

CV Super Resolution - AMD FSR

01-14

Computer Vision - CV Image Resize

12-02

Computer Vision - HDR Network

12-02

Computer Vision - UNet from Autoencoder and FCN

11-19

Computer Vision - FRC and MEMC

11-13

Excel Link to MySQL

10-22

Math ML - Entropy and Mutual Information

10-10

HMM Triology (III) - EM Algorithm

10-09

Math AI - VAE Coding

09-29

Reinforcement Learning

09-29

Windows + CUDA - PyTorch and TensorFlow

09-25

Machine Learning Database

09-19

Math AI - Deterministic and Probabilistic?

09-19

Math AI - Diffusion Generative Model Extended from VAE

08-30

Math AI - Variational Autoencoder Vs. Variational EM Algorithm

08-18

Math ML - Maximum Likelihood Vs. Bayesian

08-17

Math AI - From EM to Variational Bayesian Inference

08-15

Math AI - ML Estimation To EM Algorithm For Hidden Data

06-30

Typora and Mermaid

02-16

Math ML - Modified Softmax w/ Margin

01-16

Math AI G-CNN (Group + CNN)

05-08

Edge AI Trilogy III - Model Compression

04-05

Optimization - NN Optimization

06-19

Optimization - Manifold Gradient Descent

06-03

Optimization - Accelerate Gradient Descent

06-03

Optimization - Proxmial Gradient Descent

05-21

Math Optimization - PPO

05-11

Optimization - Gradient Descent

05-11

Math AI - Optimization II

05-01

Math Optimization - Convex Optimization

05-01

Math Optimization - Conjugate Convex

05-01

Math AI - Stochastic Differential Equation Forward

05-01

Math AI - Diffusion vs. SDE

05-01

Math AI - Stochastic Differential Equation Backward

04-29

Math AI - Stochastic Differential Equation

04-16

Math Stat I - Likelihood, Score Function, and Fisher Information

09-17

Field Theory Fundamental and Lagrangian

12-10

如何避免 L2-norm or layer norm FP16 overflow or underflow

10-09

馬克士威電磁方程和狹義相對論的相容性

10-09

Floating Point Representation

11-10

Coherent Optical Communication

11-19

Coherent Optical Communication

11-19

Git Revision Control

11-19

Quantum mechanics is just thermodynamics in imaginary time.

07-15

Gauss-Bonnet Theorem

07-07

曲率

06-23

考拉兹猜想

05-25

拉格朗日力學 - Lagrange Mechanics

04-13

微積分基本定理

03-30

複分析 and 複幾何

03-30

可視微分幾何

03-30

無限旅館悖論

02-08

曲率 Curvature

07-14

張量分析

07-12

直綫和測地綫 geodesic

07-12

非歐幾何

07-12

平行公理和平行移動 Parallel Postulate and Parallel Transport

07-12

Lin-Alg 矩陣分解

07-10

Connection and Covariant Derivative？

07-09

五次方程式無根式解

07-02

Math - 積分

04-16

Information Theory Application

01-21

Information Theory For Source Compression

12-17

Information Theory

12-17

Eigen value decomposition (EVD) 和 Single value decomposition (SVD) 的幾何意義

12-17

Fundamental theorem of GA calculus

12-17

Eigen-vector 和 Eigen-bivector 的幾何意義

12-17

無所不在的拉格朗日 - Lagrangian Everywhere

12-17

Geometric Algebra (GA) Introduction and Application

12-03

Information Theory - Constrained Noiseless Channel Capacity

01-24

Information Theory For Hash Code

01-23

Information Theory for Noisy Communication

12-17

座標系不變 (invariant), 協變 (Covariant), 和逆變 (Contravariant)

06-25

Test Obsidian Dataview Plugin

08-08

Test Obsidian Dataview Plugin

08-08

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