[AI6101] Introduction to AI & AI Ethics is a core course of MSAI, SCSE, NTU, Singapore

Overview

[AI6101] Introduction to AI & AI Ethics

====== I M P O R T A N T ======

The content in this repository should exclusively be utilized in sharing solutions for projects, communicating ideas for related problems, and references to similar assignments. If you are a student facing an assignment with the same or similar topics, you can use this repository as a reference, while the final report should include the citations of the repository. If you submit an assignment without proper acknowledgment after referring to this repository, you may be considered PLAGIARISM by your instructor, and the author will not pay ANY responsibility for this. Please refer to your teacher's and your school's instructions for the determination of academic integrity.

Moreover, if you are taking the AI6101 course, do not be stupid. You can utilize the materials here as a reference to construct your own assignment and reflect the citation to this repository in the final report. If you copy the code without citing it, you have violated NTU's academic integrity and are involved in plagiarism.

Please refer to the following links for NTU's determination of academic integrity and plagiarism:

https://ts.ntu.edu.sg/sites/intranet/dept/tlpd/ai/Pages/NTU-Academic-Integrity-Policy.aspx

https://ts.ntu.edu.sg/sites/intranet/dept/tlpd/ai/Pages/default.aspx

https://ts.ntu.edu.sg/sites/policyportal/new/Documents/All%20including%20NIE%20staff%20and%20students/Student%20Academic%20Integrity%20Policy.pdf

If you think the professor is easy to fool, think again.

====== D I S C L A I M E R ======

This repository should only be used for reasonable academic discussions. I, the owner of this repository, never and will never ALLOWING another student to copy this assignment as their own. In such circumstances, I do not violate NTU's statement on academic integrity as of the time this repository is open (16/01/2022). I am not responsible for any future plagiarism using the content of this repository.



====== I N T R O D U C T I O N ======

[AI6101] Introduction to AI & AI Ethics is a core course of Master of Science in Artificial Intelligence Graduate Programme (MSAI), School of Computer Science and Engineering (SCSE), Nanyang Technological University (NTU), Singapore. The repository corresponds to the AI6101 of Semester 1, AY2021-2022, starting from 08/2021. The instructors of this course are Prof. Bo An, Prof. Yu Han, and Dr. Melvin Chen.

The projects of this course consist of one individual Assignments, one individual Eassy, and one group Project. The topic of the assignment are shown below, and the specific score is not provided to us. Since multiple people complete the group work, I do not have the right to disclose the report and others' codes individually so that the relevant parts will be hidden.

Type Topic
Assignment Reinforcement Learning
Eassy Normative Theory
Group Project Responsible AI

====== A C K N O W L E D G E M E N T ======

All of above projects are designed by Prof. Bo An, Prof. Yu Han, and Dr. Melvin Chen.

Owner
AccSrd
AccSrd
GrailQA: Strongly Generalizable Question Answering

GrailQA is a new large-scale, high-quality KBQA dataset with 64,331 questions annotated with both answers and corresponding logical forms in different syntax (i.e., SPARQL, S-expression, etc.). It ca

OSU DKI Lab 76 Dec 21, 2022
AI-generated-characters for Learning and Wellbeing

AI-generated-characters for Learning and Wellbeing Click here for the full project page. This repository contains the source code for the paper AI-gen

MIT Media Lab 214 Jan 01, 2023
Meshed-Memory Transformer for Image Captioning. CVPR 2020

M²: Meshed-Memory Transformer This repository contains the reference code for the paper Meshed-Memory Transformer for Image Captioning (CVPR 2020). Pl

AImageLab 422 Dec 28, 2022
High-quality implementations of standard and SOTA methods on a variety of tasks.

Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo

Google 1.1k Dec 30, 2022
COVID-Net Open Source Initiative

The COVID-Net models provided here are intended to be used as reference models that can be built upon and enhanced as new data becomes available

Linda Wang 1.1k Dec 26, 2022
Machine learning algorithms for many-body quantum systems

NetKet NetKet is an open-source project delivering cutting-edge methods for the study of many-body quantum systems with artificial neural networks and

NetKet 413 Dec 31, 2022
Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020)

Forest R-CNN: Large-Vocabulary Long-Tailed Object Detection and Instance Segmentation (ACM MM 2020) Official implementation of: Forest R-CNN: Large-Vo

Jialian Wu 54 Jan 06, 2023
​ This is the Pytorch implementation of Progressive Attentional Manifold Alignment.

PAMA This is the Pytorch implementation of Progressive Attentional Manifold Alignment. Requirements python 3.6 pytorch 1.2.0+ PIL, numpy, matplotlib C

98 Nov 15, 2022
Yolo object detection - Yolo object detection with python

How to run download required files make build_image make download Docker versio

3 Jan 26, 2022
Unofficial JAX implementations of Deep Learning models

JAX Models Table of Contents About The Project Getting Started Prerequisites Installation Usage Contributing License Contact About The Project The JAX

107 Jan 05, 2023
SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging.

SweiNet SweiNet is an uncertainty-quantifying shear wave speed (SWS) estimator for ultrasound shear wave elasticity (SWE) imaging. SweiNet takes as in

Felix Jin 3 Mar 31, 2022
CUda Matrix Multiply library.

cumm CUda Matrix Multiply library. cumm is developed during learning of CUTLASS, which use too much c++ template and make code unmaintainable. So I de

49 Dec 27, 2022
Knowledge Distillation Toolbox for Semantic Segmentation

SegDistill: Toolbox for Knowledge Distillation on Semantic Segmentation Networks This repo contains the supported code and configuration files for Seg

9 Dec 12, 2022
Explore extreme compression for pre-trained language models

Code for paper "Exploring extreme parameter compression for pre-trained language models ICLR2022"

twinkle 16 Nov 14, 2022
Multi-Stage Episodic Control for Strategic Exploration in Text Games

XTX: eXploit - Then - eXplore Requirements First clone this repo using git clone https://github.com/princeton-nlp/XTX.git Please create two conda envi

Princeton Natural Language Processing 9 May 24, 2022
Code for 2021 NeurIPS --- Towards Multi-Grained Explainability for Graph Neural Networks

ReFine: Multi-Grained Explainability for GNNs This is the official code for Towards Multi-Grained Explainability for Graph Neural Networks (NeurIPS 20

Shirley (Ying-Xin) Wu 47 Dec 16, 2022
I-BERT: Integer-only BERT Quantization

I-BERT: Integer-only BERT Quantization HuggingFace Implementation I-BERT is also available in the master branch of HuggingFace! Visit the following li

Sehoon Kim 139 Dec 27, 2022
Implementation for Panoptic-PolarNet (CVPR 2021)

Panoptic-PolarNet This is the official implementation of Panoptic-PolarNet. [ArXiv paper] Introduction Panoptic-PolarNet is a fast and robust LiDAR po

Zixiang Zhou 126 Jan 01, 2023