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Course web page here: ursinusgraphics.github.io/F2024/ Notes/starter code/solution here: ursinusgraphics.github.io/F2024/ClassExercises/Week3_Reflections/index.html

Data Structures And Algorithms Course Page Here: ursinusdatastructures.github.io/F2024/ Binary Search Interactive Notes Here: ursinusdatastructures.github.io/F2024/ClassExercises/Week1_BinarySearch/ Video notes here: ursinusdatastructures.github.io/Modules/BinarySearch/Video1 Exercise here: ursinusdatastructures.github.io/Modules/BinarySearch/Exercise1 Google research article on how only 10% of...

Javascript Accidental Global Variables Bug

We provide an explanation of a Hamiltonian path through the flip graph through all possible traingulations of convex polygons, which is equivalent to all binary trees exactly once, one tree rotation at a time. This is based on a contructive proof from Joan Lucas in 1987 We summarize this proof in a writeup here and provide 16 lines of pure python code to do this: drops.dagstuhl.de/storage/00lip...

Code link here: ctraliedotcom.github.io/basicimageprocessing/LSBImgSteg.html Related assignment here: ursinus-cs174-s2023.github.io/CoursePage/Assignments/HW2_Steganography/part2.html

We can trick ResNet into thinking an image is something completely different by adding an imperceptible amount of noise. I show how to do this from scratch in code using pytorch Code/notes here: ursinus-cs477-f2023.github.io/Modules/FinalModule/TrickingResnet

Code here: github.com/ursinus-cs373-f2023/CookLevinForReal Notes here: ursinus-cs373-f2023.github.io/CoursePage/ClassExercises/Week14_CookLevin Course web page here: ursinus-cs373-f2023.github.io/CoursePage/

Assignment description here: ursinus-cs477-f2023.github.io/CoursePage/Assignments/HW7_GANUNet/part1.html Energy usage estimated using CodeCarbon codecarbon.io/

Notes here: ursinus-cs477-f2023.github.io/Modules/VAEGAN/Video5

Code/notes here: ursinus-cs477-f2023.github.io/Modules/VAEGAN/Video4 Huffman trees lab here: ursinus-cs174-s2023.github.io/CoursePage/Labs/Lab7_HuffmanTrees/

Link to notes/code: ursinus-cs477-f2023.github.io/Modules/VAEGAN/Video3 Link to kaggle dataset: www.kaggle.com/datasets/spandan2/cats-faces-64x64-for-generative-models/

Notes/code here: ursinus-cs477-f2023.github.io/Modules/VAEGAN/Video2

Notes here: ursinus-cs477-f2023.github.io/Modules/VAEGAN/Video1 Related assignment here: ursinus-cs477-f2023.github.io/CoursePage/Assignments/HW6_BYOMLP/

CS 373: P vs NP, and Why Is It Called "NP"??

CS 373: The Class NP (Certificates and Polynomial Time Verifiers)

CS 373: The Class P / Complexity Analysis of Reduction from Multitape To Single Tape Turing Machines

CS 373: A Formal Definition of Big-O

CS 373: Rice's Theorem for Undecidable Languages over Turing Machines

CS 373: Undecidable Problems (Halt, ETM, RegTM, TwoWriteTM) And Reductions from ATM

CS 271: Traveling Salesperson Art / 2-Opt "Crossing Canceling" Heuristic for Metric TSP Problems

CS 271: Delaunay Triangulations in Scipy

CS 271: Traveling Salesperson And 2-Approximation with DFS on MST

CS 271: Fast Plant Cell Image Segmentation Using Depth-First Search

CS 271: Breadth-First Search And Depth-First Search

Data Structures: The Magical Adjacency Matrix Representation for Graphs

Data Structures: Adjacency Graph Data Structure

Data Structures: Undirected Graphs, EdgeSet Graph Data Structure

CS 477 AI: Derivation of Matrix Derivatives for Backpropagation in General Multilayer Perceptrons

CS 477 AI: Backpropagation on 1D Multilayer Perceptrons