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How I Study AI - Learn AI Papers & Lectures the Easy Way

Concepts6

Groups

๐Ÿ“Linear Algebra15๐Ÿ“ˆCalculus & Differentiation10๐ŸŽฏOptimization14๐ŸŽฒProbability Theory12๐Ÿ“ŠStatistics for ML9๐Ÿ“กInformation Theory10๐Ÿ”บConvex Optimization7๐Ÿ”ขNumerical Methods6๐Ÿ•ธGraph Theory for Deep Learning6๐Ÿ”ตTopology for ML5๐ŸŒDifferential Geometry6โˆžMeasure Theory & Functional Analysis6๐ŸŽฐRandom Matrix Theory5๐ŸŒŠFourier Analysis & Signal Processing9๐ŸŽฐSampling & Monte Carlo Methods10๐Ÿง Deep Learning Theory12๐Ÿ›ก๏ธRegularization Theory11๐Ÿ‘๏ธAttention & Transformer Theory10๐ŸŽจGenerative Model Theory11๐Ÿ”ฎRepresentation Learning10๐ŸŽฎReinforcement Learning Mathematics9๐Ÿ”„Variational Methods8๐Ÿ“‰Loss Functions & Objectives10โฑ๏ธSequence & Temporal Models8๐Ÿ’ŽGeometric Deep Learning8

Category

๐Ÿ”ทAllโˆ‘Mathโš™๏ธAlgo๐Ÿ—‚๏ธDS๐Ÿ“šTheory

Level

AllBeginnerIntermediate
โš™๏ธAlgorithmIntermediate

Functional Graph

A functional graph is a directed graph where every node has exactly one outgoing edge, so repeatedly following edges from any start eventually loops into a cycle.

#functional graph#successor graph#cycle detection+10
โš™๏ธAlgorithmIntermediate

LCA - Binary Lifting

Binary lifting precomputes 2^k ancestors for every node so we can jump upward in powers of two.

#lca
Advanced
Filtering by:
#binary lifting
#binary lifting
#tree
+12
โš™๏ธAlgorithmIntermediate

Bridge Tree

A bridge tree is built by contracting every 2-edge-connected component of an undirected graph into a single node, leaving only bridges as edges between nodes.

#bridge tree#2-edge-connected components#bridges+12
โš™๏ธAlgorithmIntermediate

Tree Distances and Diameter

Tree diameter is the longest simple path in a tree and can be found with two BFS/DFS runs.

#tree diameter#tree center#eccentricity+12
โš™๏ธAlgorithmIntermediate

Lowest Common Ancestor (LCA)

The Lowest Common Ancestor (LCA) of two nodes in a rooted tree is the deepest node that is an ancestor of both.

#lowest common ancestor#binary lifting#euler tour+12
โš™๏ธAlgorithmIntermediate

Minimum Spanning Tree - Kruskal

Kruskalโ€™s algorithm builds a minimum spanning tree (MST) by sorting all edges by weight and greedily picking the next lightest edge that does not form a cycle.

#kruskal#minimum spanning tree#mst+11