GE2340 project source code without credentials.

Last update: Feb 10, 2022

Related tags

Deep Learning GE2340-Project-Public

Overview

GE2340-Project-Public

GE2340 project source code without credentials.

Run the bot.py to start the bot

Telegram: @jasperwong_ge2340_bot

If the bot does not respond, the server might be rebooting. Please wait around 2 minutes.

Reboot Schedule:

00:00
02:00
04:00
06:00
10:00
12:00
14:00
16:00
18:00
20:00
22:00

Code for Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022)

Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022) We consider how a user of a web servi

20 Aug 21, 2022

PaddleRobotics is an open-source algorithm library for robots based on Paddle, including open-source parts such as human-robot interaction, complex motion control, environment perception, SLAM positioning, and navigation.

简体中文 | English PaddleRobotics paddleRobotics是基于paddle的机器人开源算法库集，包括人机交互、复杂运动控制、环境感知、slam定位导航等开源算法部分。人机交互主动多模交互技术TFVT-HRI 主动多模交互技术是通过视觉、语音、触摸传感器等输入机器人

185 Dec 26, 2022

Source-to-Source Debuggable Derivatives in Pure Python

Tangent Tangent is a new, free, and open-source Python library for automatic differentiation. Existing libraries implement automatic differentiation b

2.2k Jan 1, 2023

Like a cowsay but without cows!

Foxsay This is a simple program that generates pictures of a cute fox with a message. It is like a cowsay but without cows! Fox girls are better! Usag

28 Feb 20, 2022

A framework for joint super-resolution and image synthesis, without requiring real training data

SynthSR This repository contains code to train a Convolutional Neural Network (CNN) for Super-resolution (SR), or joint SR and data synthesis. The met

83 Jan 1, 2023

Image morphing without reference points by applying warp maps and optimizing over them.

Differentiable Morphing Image morphing without reference points by applying warp maps and optimizing over them. Differentiable Morphing is machine lea

380 Dec 19, 2022

BBB streaming without Xorg and Pulseaudio and Chromium and other nonsense (heavily WIP)

BBB Streamer NG? Makes a conference like this... ...streamable like this! I also recorded a small video showing the basic features: https://www.youtub

60 Oct 21, 2022

Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.

InfoPro-Pytorch The Information Propagation algorithm for training deep networks with local supervision. (ICLR 2021) Revisiting Locally Supervised Lea

78 Dec 27, 2022

Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance

Models for natural language understanding (NLU) tasks often rely on the idiosyncratic biases of the dataset, which make them brittle against test cases outside the training distribution.

22 Jan 2, 2023

Owner

Working as a software engineer intern at a startup based in Hong Kong.

GitHub

This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.

SLATE This is the official source code for SLATE. We provide the code for the model, the training code and a dataset loader for the 3D Shapes dataset.

66 Dec 26, 2022

Project Aquarium is a SUSE-sponsored open source project aiming at becoming an easy to use, rock solid storage appliance based on Ceph.

Project Aquarium Project Aquarium is a SUSE-sponsored open source project aiming at becoming an easy to use, rock solid storage appliance based on Cep

73 Jul 21, 2022

a delightful machine learning tool that allows you to train, test and use models without writing code

igel A delightful machine learning tool that allows you to train/fit, test and use models without writing code Note I'm also working on a GUI desktop

3k Jan 5, 2023

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

Translated in ???? Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on

8.7k Jan 5, 2023

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

Translated in ???? Korean/ Ludwig is a toolbox that allows users to train and test deep learning models without the need to write code. It is built on

8.7k Dec 31, 2022

Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation

PLOP: Learning without Forgetting for Continual Semantic Segmentation This repository contains all of our code. It is a modified version of Cermelli e

116 Dec 14, 2022

Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip

922 Jan 1, 2023

Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

ViLT Code for the paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision" Install pip install -r requirements.txt pip

922 Jan 1, 2023

This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re

113 Dec 23, 2022

This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"

697 Jan 6, 2023

GE2340 project source code without credentials.

Related tags

Overview

GE2340-Project-Public

Run the bot.py to start the bot

Telegram: @jasperwong_ge2340_bot

If the bot does not respond, the server might be rebooting. Please wait around 2 minutes.

You might also like...

Code for Private Recommender Systems: How Can Users Build Their Own Fair Recommender Systems without Log Data? (SDM 2022)

PaddleRobotics is an open-source algorithm library for robots based on Paddle, including open-source parts such as human-robot interaction, complex motion control, environment perception, SLAM positioning, and navigation.

Source-to-Source Debuggable Derivatives in Pure Python

Like a cowsay but without cows!

A framework for joint super-resolution and image synthesis, without requiring real training data

Image morphing without reference points by applying warp maps and optimizing over them.

BBB streaming without Xorg and Pulseaudio and Chromium and other nonsense (heavily WIP)

Learning recognition/segmentation models without end-to-end training. 40%-60% less GPU memory footprint. Same training time. Better performance.

Mind the Trade-off: Debiasing NLU Models without Degrading the In-distribution Performance

Owner

This is the official source code for SLATE. We provide the code for the model, the training code, and a dataset loader for the 3D Shapes dataset. This code is implemented in Pytorch.

Project Aquarium is a SUSE-sponsored open source project aiming at becoming an easy to use, rock solid storage appliance based on Ceph.

a delightful machine learning tool that allows you to train, test and use models without writing code

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

Ludwig is a toolbox that allows to train and evaluate deep learning models without the need to write code.

Official code of CVPR 2021's PLOP: Learning without Forgetting for Continual Semantic Segmentation

Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

Code for the ICML 2021 paper: "ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision"

This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data

This repository contains the code for the CVPR 2020 paper "Differentiable Volumetric Rendering: Learning Implicit 3D Representations without 3D Supervision"