# 1. Installing Maven & Pandas First, please install Java (JDK11) and Python 3 if they are not already. Next, make sure that Maven (for importing JGraphT) and Pandas(for data analysis) are installed. To install Maven on Ubuntu, type the following commands on terminal: sudo apt-get update sudo apt-get install maven For Pandas, type the following: pip3 install pandas ( sudo apt-get install python3-pip if pip is not installed already) # 2. Compilation Type the following to compile this project: mvn compile # 3. Running the code Below is the command for running tests for SNAP(DIMACS) and grid data. java -Xms24G -Xmx48G -Xmn36G -Xss1G -cp $CLASSPATHS shell.TestSNAP (the filename of data; just the name and not the path) (# of tests) (randomization seed) java -Xms32G -Xmx64G -Xmn48G -Xss1G -cp $CLASSPATHS shell.TestGrid (Maximum dimension) (dimension increment) [List of the values for k, space-separated] You may change the randomization seed (vertex selection) to assess reproducibility. (In our experiment, the seed was set to 2021.) For the data, check "src/SNAP(or DIMACS)". Output "test_result.csv" will be saved on "target" directory. Check if 'CLASSPATHS' is set properly. Please refer to " sample.sh " for examples & further details. #4. Obtaining average processing time and diversity First, move to the target directory. Then run get_averages.py python3 get_averages (.csv file name) [list of the values for k, space-separated. Optional parameter.]
Diverse graph algorithms implemented using JGraphT library.
Overview
A robotic arm that mimics hand movement through MediaPipe tracking.
La-Z-Arm A robotic arm that mimics hand movement through MediaPipe tracking. Hardware NVidia Jetson Nano Sparkfun Pi Servo Shield Micro Servos Webcam
A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maximum bidding
Business Problem A commany has recently introduced a new type of bidding, the average bidding, as an alternative to the bid given to the current maxim
NAVER BoostCamp Final Project
CV 14조 final project Super Resolution and Deblur module Inference code & Pretrained weight Repo SwinIR Deblur 실행 방법 streamlit run WebServer/Server_SRD
Distributed DataLoader For Pytorch Based On Ray
Dpex——用户无感知分布式数据预处理组件 一、前言 随着GPU与CPU的算力差距越来越大以及模型训练时的预处理Pipeline变得越来越复杂,CPU部分的数据预处理已经逐渐成为了模型训练的瓶颈所在,这导致单机的GPU配置的提升并不能带来期望的线性加速。预处理性能瓶颈的本质在于每个GPU能够使用的C
Fine-Tune EleutherAI GPT-Neo to Generate Netflix Movie Descriptions in Only 47 Lines of Code Using Hugginface And DeepSpeed
GPT-Neo-2.7B Fine-Tuning Example Using HuggingFace & DeepSpeed Installation cd venv/bin ./pip install -r ../../requirements.txt ./pip install deepspe
chainladder - Property and Casualty Loss Reserving in Python
chainladder (python) chainladder - Property and Casualty Loss Reserving in Python This package gets inspiration from the popular R ChainLadder package
Implementation of ResMLP, an all MLP solution to image classification, in Pytorch
ResMLP - Pytorch Implementation of ResMLP, an all MLP solution to image classification out of Facebook AI, in Pytorch Install $ pip install res-mlp-py
Decorators for maximizing memory utilization with PyTorch & CUDA
torch-max-mem This package provides decorators for memory utilization maximization with PyTorch and CUDA by starting with a maximum parameter size and
code for EMNLP 2019 paper Text Summarization with Pretrained Encoders
PreSumm This code is for EMNLP 2019 paper Text Summarization with Pretrained Encoders Updates Jan 22 2020: Now you can Summarize Raw Text Input!. Swit
Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions
Aquarius Aquarius - Enabling Fast, Scalable, Data-Driven Virtual Network Functions NOTE: We are currently going through the open-source process requir
A system used to detect whether a person is wearing a medical mask or not.
Mask_Detection_System A system used to detect whether a person is wearing a medical mask or not. To open the program, please follow these steps: Make
DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation
DCT-Mask: Discrete Cosine Transform Mask Representation for Instance Segmentation This project hosts the code for implementing the DCT-MASK algorithms
Project dự đoán giá cổ phiếu bằng thuật toán LSTM gồm: code train và code demo
Web predicts stock prices using Long - Short Term Memory algorithm Give me some start please!!! User interface image: Choose: DayBegin, DayEnd, Stock
PyTorch Lightning implementation of Automatic Speech Recognition
lasr Lightening Automatic Speech Recognition An MIT License ASR research library, built on PyTorch-Lightning, for developing end-to-end ASR models. In
Official PyTorch Implementation of "Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs". NeurIPS 2020.
Self-supervised Auxiliary Learning with Meta-paths for Heterogeneous Graphs This repository is the implementation of SELAR. Dasol Hwang* , Jinyoung Pa
Official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution"
RealBasicVSR [Paper] This is the official repository of "Investigating Tradeoffs in Real-World Video Super-Resolution, arXiv". This repository contain
Unadversarial Examples: Designing Objects for Robust Vision
Unadversarial Examples: Designing Objects for Robust Vision This repository contains the code necessary to replicate the major results of our paper: U
Code for the paper: Learning Adversarially Robust Representations via Worst-Case Mutual Information Maximization (https://arxiv.org/abs/2002.11798)
Representation Robustness Evaluations Our implementation is based on code from MadryLab's robustness package and Devon Hjelm's Deep InfoMax. For all t
SeqTR: A Simple yet Universal Network for Visual Grounding
SeqTR This is the official implementation of SeqTR: A Simple yet Universal Network for Visual Grounding, which simplifies and unifies the modelling fo
Instant neural graphics primitives: lightning fast NeRF and more
Instant Neural Graphics Primitives Ever wanted to train a NeRF model of a fox in under 5 seconds? Or fly around a scene captured from photos of a fact