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Fast and Accurate Triangle Counting in Graph Streams Using Predictions (ICDM 2024)
Fast and memory-efficient clustering + coreset construction, including fast distance kernels for Bregman and f-divergences.
ESA 2022, "An Empirical Evaluation of k-Means Coresets".
List of Computer Science courses with video lectures.
This course is an overview of applied causal inference.
TRIEST: TRIÈST: Counting Local and Global Triangles in Fully-Dynamic Streams with Fixed Memory Size
WRS: Waiting Room Sampling for Accurate Triangle Counting in Real Graph Streams (ICDM'17 & VLDBJ'20)
Platform for designing and evaluating Graph Neural Networks (GNN)
Code repository for the paper "Improved Learning-augmented Algorithms for k-means and k-medians Clustering" (ICLR 2023)
Repository of LFN course's project a.y. 2022/23
Implementation of Diffusion Convolutional Recurrent Neural Network in Tensorflow
T81-558: Keras - Applications of Deep Neural Networks @Washington University in St. Louis
Python Implementation of Reinforcement Learning: An Introduction
Diffusion Convolutional Recurrent Neural Network Implementation in PyTorch
Python package built to ease deep learning on graph, on top of existing DL frameworks.
[IJCAI'18] Spatio-Temporal Graph Convolutional Networks
用opencv的dnn模块做yolov5目标检测,包含C++和Python两个版本的程序,优化后的
SSD on CPU using subset of Egohands Dataset
One-way carsharing optimization using LP and stable matching