[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
Lava-DL, but with PyTorch-Lightning flavour

Deep learning project seed Use this seed to start new deep learning / ML projects. Built in setup.py Built in requirements Examples with MNIST Badges

Sami BARCHID 4 Oct 31, 2022
Toolbox of models, callbacks, and datasets for AI/ML researchers.

Pretrained SOTA Deep Learning models, callbacks and more for research and production with PyTorch Lightning and PyTorch Website • Installation • Main

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Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification

Dealing With Misspecification In Fixed-Confidence Linear Top-m Identification This repository is the official implementation of [Dealing With Misspeci

0 Oct 25, 2021
Learnable Boundary Guided Adversarial Training (ICCV2021)

Learnable Boundary Guided Adversarial Training This repository contains the implementation code for the ICCV2021 paper: Learnable Boundary Guided Adve

DV Lab 27 Sep 25, 2022
Official implementation for ICDAR 2021 paper "Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer"

Handwritten Mathematical Expression Recognition with Bidirectionally Trained Transformer Description Convert offline handwritten mathematical expressi

Wenqi Zhao 87 Dec 27, 2022
A curated list of awesome neural radiance fields papers

Awesome Neural Radiance Fields A curated list of awesome neural radiance fields papers, inspired by awesome-computer-vision. How to submit a pull requ

Yen-Chen Lin 3.9k Dec 27, 2022
CONetV2: Efficient Auto-Channel Size Optimization for CNNs

CONetV2: Efficient Auto-Channel Size Optimization for CNNs Exciting News! CONetV2: Efficient Auto-Channel Size Optimization for CNNs has been accepted

Mahdi S. Hosseini 3 Dec 13, 2021
Some pvbatch (paraview) scripts for postprocessing OpenFOAM data

pvbatchForFoam Some pvbatch (paraview) scripts for postprocessing OpenFOAM data For every script there is a help message available: pvbatch pv_state_s

Morev Ilya 2 Oct 26, 2022
Prompts - Read a textfile of prompts and import into anki via ankiconnect

prompts read a textfile of prompts and import into anki via ankiconnect Usage In

Alexander Cobleigh 2 Jul 28, 2022
ManipNet: Neural Manipulation Synthesis with a Hand-Object Spatial Representation - SIGGRAPH 2021

ManipNet: Neural Manipulation Synthesis with a Hand-Object Spatial Representation - SIGGRAPH 2021 Dataset Code Demos Authors: He Zhang, Yuting Ye, Tak

HE ZHANG 194 Dec 06, 2022
[NeurIPS2021] Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks

Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks Code for NeurIPS 2021 Paper "Exploring Architectural Ingredients of A

Hanxun Huang 26 Dec 01, 2022
A `Neural = Symbolic` framework for sound and complete weighted real-value logic

Logical Neural Networks LNNs are a novel Neuro = symbolic framework designed to seamlessly provide key properties of both neural nets (learning) and s

International Business Machines 138 Dec 19, 2022
Multi-Glimpse Network With Python

Multi-Glimpse Network Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention arXiv Require

9 May 10, 2022
Software that can generate photos from paintings, turn horses into zebras, perform style transfer, and more.

CycleGAN PyTorch | project page | paper Torch implementation for learning an image-to-image translation (i.e. pix2pix) without input-output pairs, for

Jun-Yan Zhu 11.5k Dec 30, 2022
A library for answering questions using data you cannot see

A library for computing on data you do not own and cannot see PySyft is a Python library for secure and private Deep Learning. PySyft decouples privat

OpenMined 8.5k Jan 02, 2023
PyTorch - Python + Nim

Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+

Giovanni Petrantoni 425 Dec 22, 2022
Google Brain - Ventilator Pressure Prediction

Google Brain - Ventilator Pressure Prediction https://www.kaggle.com/c/ventilator-pressure-prediction The ventilator data used in this competition was

Samuele Cucchi 1 Feb 11, 2022
Pytorch implementation for "Density-aware Chamfer Distance as a Comprehensive Metric for Point Cloud Completion" (NeurIPS 2021)

Density-aware Chamfer Distance This repository contains the official PyTorch implementation of our paper: Density-aware Chamfer Distance as a Comprehe

Tong WU 93 Dec 15, 2022
A Jinja extension (compatible with Flask and other frameworks) to compile and/or compress your assets.

A Jinja extension (compatible with Flask and other frameworks) to compile and/or compress your assets.

Jayson Reis 94 Nov 21, 2022
A TensorFlow implementation of the Mnemonic Descent Method.

MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.

123 Oct 07, 2022