You will choose your assignment from the following two groups: Regular Graphs and AI Based Graphs ******* Regular Graphs (If you do not want to go in AI path) ********* - Suggestion 1 : Implementation of a Shortest Spanning Tree (SPT) and its demonstration You can implement many algorithms of SPT and compare the results (performance, space requirements, etc.) - Suggestion 2 : Implementation of a Traveller Salesman Problem (TSP) and its demonstration You can implement many algorithms (greedy, simulated annealing, ant colony, genetic algorithms etc.) of SPT and compare the results (performance, space requirements, etc.) - Suggestion 3 : Implementation of Dijkstra's Algorithm and Its demonstration You can implement the algorithm and its variants/similars and compare the results (performance, space requirements, etc.) - Suggestion 4 : Implementation of A* Algorithm and Its demonstration You can implement the algorithm and its variants/smilars and compare the results (performance, space requirements, etc.) - Suggestion 5 : If you want to do other stuff, please first confirm with me. ******* AI Graphs (If you do want to go in AI path) ********* - NOTE 1 You can use PyG (PyTourch Gemoetric) or its C/CPP libraries for your programming language. The safest bat would be impelemtning in python. - NOTE 2 You will do your implementation in Google Collab. When you are finished, you can just submit your link to the saved notebook on your Google Drive or in any other medium. - NOTE 3 You can directly submit the notebook, downloading from Google Collab, as an ipynb file - Suggestion 1 : Implementation of PageRank with Graph Neural Networks You can implement any (or your own) PageRank algorithm (https://en.wikipedia.org/wiki/PageRank) - Suggestion 2 : Graph Link Detection with Graph Neural Networks You will check a graph data structure for a possible link addition. Like friend suggestion in social media. - Suggestion 3 : Graph Node Classification with Graph Neural Networks You will check a graph data structure for a possible node classes. Like social group finding in social media. - Suggestion 4 : Anomaly Detection with Graph Neural Networks You will check a graph data structure for a possible anomaly. Like finding a node that possibly not belonging to the graph. - Suggestion 5 : Temporal Graph Neural Networks Temporal Graph Neural Networks takes time as an input. It tackles the problem when the graph changes with time. You can implement any algorithm (anomaly detection, classification, ..etc). - Suggestion 6 : If you want to do other stuff, please first confirm with me. Best of lucks! - NOTE 1: From now on, we will not come to the class. Please work on your final assignment. - NOTE 2: I will be at the classroom at class hours, if you need anything. - NOTE 3: You will have till final, but final dates are not clear yet, so deadline can change.