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Algorithms
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Base-indexed Addressing Mode
Basic Structure of Golang Programs
Binary Search
Bit Accuracy
Boolean Function
Boolean Logic
Boolean Satisfiability Problem (SAT)
Bubble Sort
C Programing Language
Church–Turing Thesis
Circuits (Computer Science)
Combinational Circuits
Complexity Classes
Computability
Computational Abstraction
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Computational Thinking
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Data Representation
Decision Problem
Divide-and-conquer Algorithm
Flip-flop
Full Adder
Fundamental Theorem of Software Engineering
Gödel's Incompleteness Theorem
Golang
Golang Basic Types and Operators
Indirection
Instruction Pipeline
Instruction Set
Introduction to Computer Science
Knuth's Definition of Algorithm
Linux Permission
Linux References
Logic Gate
Master Theorem
Mathematical Logic
Memory Address
Multiplication Algorithm
Naming and Namespace
P Versus NP Problem
Pointer
Predicate Logic
Print Format
Protocol Stack
Quick Sort
Ripple-carry Adder
RSA Encryption
Seamless Transition
Sequential Circuits
Serial Adder
Software Stack on a von Neumann Computer
Space Complexity
Stable Marriage Problem
Ternary Search
Time Complexity
Turing Machine
Unicode
UTF-8
von Neumann Architecture
Machine Learning
Activation Functions
Bandit Slippery Walk (BSW) Environment
Bandit Walk (BW) Environment
Batch Normalization
Computer Vision
Convolutional Neural Networks (CNNs)
Cross Entropy Loss
Deep Learning
Dynamic Programming
Epsilon-Greedy Algorithm
ERM Learning
Frozen Lake (FL) Environment
Gird World (GW) Environment
Global Pooling
Gradient Ascent
Gradient Descent
Hands-on Reinforcement Learning
He Initialization
Introduction to Reinforcement Learning
Layer Normalization
Long Short-Term Memory (LSTM)
Loss Functions
Machine Learning
Markov Decision Process, MDP
Markov Property
Multi-armed Bandit
Multilayer Perceptrons
Non-maximum Suppression
Object Detection
Occupancy Measure
OpenAI Gym toolkit
PAC learning model
Rectified Linear Unit (ReLU)
Recurrent Neural Networks (RNNs)
Reinforcement Learning
Semantic Segmentation
Sigmoid Function
Softmax
Stable Activations and Gradients in Deep Learning
Stochastic Gradient Descent (SGD)
Temporal Difference, TD
Thompson Sampling Algorithm
Understanding Machine Learning - From Theory to Algorithms
Upper Confidence Bound Algorithm, UCB
Word Embedding
Xavier Initialization
Mathematics
23 Fall Analysis Notes
Abelian Group
Abstraction
Adjugate Matrix
Affine Transformation
Analytical Geometry in Space
Basis and Dimension
Bayes' Theorem
Bernoulli and Binomial Distributions
Bessel Inequality
Beta Distribution
Bilinear Form
Bounded Set
Cardinality of Sets
Cartesian Products
Category
Category Theory
Cayley-Hamilton Theorem
Characteristic of a Ring
Characteristic Polynomial
Circulant Matrix
Compact Space
Complex Numbers
Conditional Extremum
Conditional Probability
Continuous Function
Continuous Random Variables
Convolution
Convolution (Continuous)
Convolution (Discrete)
Coordinate Transformation
Cover (Topology)
Curve Integral
Cyclic Subspace
Diagonal Matrix
Diagonalization
Differential of Mappings
Differential of Multivariable Functions
Dirac Delta Function
Discrete Mathematics
Distributions of Random Variable
Division Ring
Dual Space
Eigenvectors and Characteristic Polynomial
Elementary Divisors
Equivalence Relation
Euclidean Space
Euler Integral
Euler's Formula
Euler's Theorem
Euler's Totient Function
Exgcd - Extended Euclidean Algorithm
Exponential Distribution
Extremum of Multivariable Functions
Fermat's Little Theorem
Field
Fourier Series
Fourier Transformation
Function Series
Fundamental Theorem of Symmetric Polynomials
Gamma Distribution
Gauss's Divergence Theorem
Gauss's Lemma and Eisenstein's Irreducibility Criterion
Gaussian Integral
General Definition of Probability
General Linear Group
General Linear Position
Generalized Eigenvectors and Eigenspaces
Geometric and Hypergeometric Distributions
Graph
Group
Group Theory
Hamilton Quaternion
Hermitian Conjugate
Hoeffding's Inequality
Householder Transformation and Matrix
Implicit Function
Improper Integrals
Indexed Family
Indicator Function
Injective, Surjective and Bijective
Integral Domain
Integrals with Parameters
Invariant Subspace
Inversion
Joint Distributions
Jordan Canonical Form
Jordan Canonical Form Life Saver
Kronecker Delta
Kullback–Leibler Divergence
Least Squares Method
Lie Algebra
Lie Group
Limit of Multivariable Functions
Linear Algebra
Linear Algebra 23 Fall Final
Linear Algebra 24 Spring Final
Linear Algebra 24 Spring Midterm
Linear Isomorphism
Linear Map
Linear Map on Linear Independent Vectors
Linear Operator
Linear Space
Logic and Proofs
Logic Equivalences
Mathematical Analysis
Mathematical Analysis 23 Fall Final
Mathematical Analysis 24 Spring Final
Mathematical Analysis 24 Spring Midterm
Mathematics
Matrix Determinant
Matrix Exponential
Matrix Inverse
Matrix Minor
Matrix Rank
Matrix Representation of Linear Map
Matrix Trace
Methods of Proving Theorems
Metric Space
Minimal Polynomial
Modular Inverse
Monoid
Multiple Integral
Multisets
Multivariate Polynomial Ring
Nash Equilibrium
Nested Interval Theorem
Normal Distribution (Gaussian Distribution)
Normal Operator and Normal Matrix
Number Theory
Orthogonal Canonical Forms
Orthogonal Group
Partially Ordered Set
Permutation
Planar Point Set
Poisson Distribution
Polynomial Series
Power Series
Power Sets
Predicates and Quantifiers
Prime Element
Probability Theory
Projection
Propositional Logic
Quadratic Forms
Quotient Space
Random Variables
Real Quadratic Forms
Ring
Rules of Inference
Set
Skew-symmetric Bilinear Form and Sympletic Plane
Smooth Function
Smooth Manifold
Special Linear Group
Special Orthogonal Group
Special Unitary Group
Spectral Decomposition
Stationary Point
Stirling's Formula
Stokes' Curl Theorem
Subsequence
Surface Integral
Sylvester Inequality
Symmetric Group
Symplectic Group
Table Method for Integration by Parts
Taylor Series of Multivariable Functions
Topological Space
Tricks on Vectors
Uniform Distributions
Unimodality
Unique Factorization Domain, UFD
Unitary Group
Physics
AC Power
Amplitude-splitting Interferometer
Angular Magnification
Blackbody Radiation
Boltzmann Distribution
Boundary Condition
Conductors and Dielectrics in Electric Fields
Crystal Polarization Optics
Depth of Field, DOF
Diffraction of Light
Electrodynamics
Electromagnetic Induction
Electromagnetic Waves and Energy Flux Density
Electrostatic Field
Entropy
Equation of State
Equipartition Theorem
Foundations of Applied Optics
Fourier Optics
Fourier Transformation in Optics
Fraunhofer Diffraction
Free Energy
Fresnel Diffraction
Fresnel Equations
Grating
Hydromechanics
Imagery
Interference of Waves
Introduction to Geometrical Optics
Introduction to Molecular Dynamics Theory
Introduction to Optics
Introduction to Photometry
Introduction to Thermodynamics
Laser
Laws of Thermodynamics
Light Absorption
Light Dispersion
Liquid
Magnetic Circuit
Magnetic Fields in Matter
Maxwell Distribution of Speed
Maxwell Relationship
Mean Free Path
Mechanics
Multi-beam Interference
Numerical Aperture
Optical Information
Optical Systems
Optics
Optics Final Review
Optics Midterm Review
Optics Midterm Test
Phase Transition
Physics
Polarization
Processes of Ideal Gases
Radiometry
Representation of Electromagnetic Waves
Resonant Circuit and Quality Factor Q
Response Function
Rigid Body
Scattering of Light
Special Relativity
Standard State
Static Magnetic Field
Steady Current
Temperature and Equilibrium State
The First Law of Thermodynamics
The Second Law of Thermodynamics
The Third Law of Thermodynamics
Thermodynamic Temperature Scale
Thermodynamics
Thermodynamics Final
Thermodynamics Midterm Review
Three-phase Circuit
Transport Process of Gases
Vacuum Level
Van der Waals Equation of State
Vibrations and Waves
Wavefront-splitting Interferometer
Project Notes
How to Draw UCAS via Fourier Series
Researches
Papers
A ConvNet for the 2020s
An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale
Asymmetric Non-local Neural Networks for Semantic Segmentation
Attention Is All You Need
BEiT: BERT Pre-Training of Image Transformers
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
BiSeNet V2: Bilateral Network with Guided Aggregation for Real-time Semantic Segmentation
BiSeNet: Bilateral Segmentation Network for Real-time Semantic Segmentation
CCNet: Criss-Cross Attention for Semantic Segmentation
Context Encoding for Semantic Segmentation
Deep High-Resolution Representation Learning for Visual Recognition
DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
Dual Attention Network for Scene Segmentation
Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation
End-to-End Object Detection with Transformers
Fast R-CNN
Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks
Feature Pyramid Networks for Object Detection
Focal Loss for Dense Object Detection
Fully Convolutional Networks for Semantic Segmentation
GCNet: Non-local Networks Meet Squeeze-Excitation Networks and Beyond
Generative Adversarial Networks
ICNet for Real-Time Semantic Segmentation on High-Resolution Images
Learning Transferable Visual Models From Natural Language Supervision
Mask R-CNN
Masked Autoencoders Are Scalable Vision Learners
Masked-attention Mask Transformer for Universal Image Segmentation
Non-local Neural Networks
OneFormer: One Transformer to Rule Universal Image Segmentation
Per-Pixel Classification is Not All You Need for Semantic Segmentation
PointRend: Image Segmentation as Rendering
PSANet: Point-wise Spatial Attention Network for Scene Parsing
Pyramid Scene Parsing Network
R-FCN: Object Detection via Region-based Fully Convolutional Networks
RefineNet: Multi-Path Refinement Networks for High-Resolution Semantic Segmentation
Rethinking Atrous Convolution for Semantic Image Segmentation
Rich feature hierarchies for accurate object detection and semantic segmentation
SAM 2: Segment Anything in Images and Videos
SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers
Segment Anything
Segmentation Transformer: Object-Contextual Representations for Semantic Segmentation
Segmenter: Transformer for Semantic Segmentation
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
SSD: Single Shot MultiBox Detector
Swin Transformer: Hierarchical Vision Transformer using Shifted Windows
Training Region-based Object Detectors with Online Hard Example Mining
U-Net: Convolutional Networks for Biomedical Image Segmentation
Vision Transformers for Dense Prediction
YOLO9000: Better, Faster, Stronger
YOLOv3: An Incremental Improvement
You Only Look Once: Unified, Real-Time Object Detection
Research Index
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