Least Square Calibration for Peer Reviews

Related tags

Deep LearningLSC
Overview

Least Square Calibration for Peer Reviews

Requirements

  • gurobipy -> for solving convex programs
  • GPy -> for Bayesian baseline
  • numpy
  • pandas

To generate paper review data, execute

python generate_data.py

which will generate 20 trials of paper review data in the data/linear folder.

To generate data from the peer grading dataset, execute

python convert_peer_grade.py

To run a model on these 20 trials, execute

python main.py --m $model

where $model can be one of LSC_mono, LSC_card, QP, bayesian

To run a model in the noisy setting, change noise_std at line 183 of main.py to 0.5, and then execute the command above.

Owner
Sigma [email protected]
Research projects in the Strategic IntelliGence for Machine Agents (SIGMA) Lab
Sigma <a href=[email protected]">
PyTorch source code for Distilling Knowledge by Mimicking Features

LSHFM.detection This is the PyTorch source code for Distilling Knowledge by Mimicking Features. And this project contains code for object detection wi

Guo-Hua Wang 4 Dec 17, 2022
Emotion Recognition from Facial Images

Reconhecimento de Emoções a partir de imagens faciais Este projeto implementa um classificador simples que utiliza técncias de deep learning e transfe

Gabriel 2 Feb 09, 2022
Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

Offcial repository for the IEEE ICRA 2021 paper Auto-Tuned Sim-to-Real Transfer.

47 Jun 30, 2022
Fermi Problems: A New Reasoning Challenge for AI

Fermi Problems: A New Reasoning Challenge for AI Fermi Problems are questions whose answer is a number that can only be reasonably estimated as a prec

AI2 15 May 28, 2022
Hand Gesture Volume Control | Open CV | Computer Vision

Gesture Volume Control Hand Gesture Volume Control | Open CV | Computer Vision Use gesture control to change the volume of a computer. First we look i

Jhenil Parihar 3 Jun 15, 2022
MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution

Octave Convolution MXNet implementation for: Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octave Convolution Imag

Meta Research 549 Dec 28, 2022
This repository contains the code for the CVPR 2021 paper "GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields"

GIRAFFE: Representing Scenes as Compositional Generative Neural Feature Fields Project Page | Paper | Supplementary | Video | Slides | Blog | Talk If

1.1k Dec 30, 2022
Code to reproduce the experiments from our NeurIPS 2021 paper " The Limitations of Large Width in Neural Networks: A Deep Gaussian Process Perspective"

Code To run: python runner.py new --save SAVE_NAME --data PATH_TO_DATA_DIR --dataset DATASET --model model_name [options] --n 1000 - train - t

Geoff Pleiss 5 Dec 12, 2022
coldcuts is an R package to automatically generate and plot segmentation drawings in R

coldcuts coldcuts is an R package that allows you to draw and plot automatically segmentations from 3D voxel arrays. The name is inspired by one of It

2 Sep 03, 2022
Session-aware Item-combination Recommendation with Transformer Network

Session-aware Item-combination Recommendation with Transformer Network 2nd place (0.39224) code and report for IEEE BigData Cup 2021 Track1 Report EDA

Tzu-Heng Lin 6 Mar 10, 2022
StyleGAN-Human: A Data-Centric Odyssey of Human Generation

StyleGAN-Human: A Data-Centric Odyssey of Human Generation Abstract: Unconditional human image generation is an important task in vision and graphics,

stylegan-human 762 Jan 08, 2023
A machine learning malware analysis framework for Android apps.

🕵️ A machine learning malware analysis framework for Android apps. ☢️ DroidDetective is a Python tool for analysing Android applications (APKs) for p

James Stevenson 77 Dec 27, 2022
Official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION.

IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSUMPTION This is the official repository of IMPROVING DEEP IMAGE MATTING VIA LOCAL SMOOTHNESS ASSU

电线杆 14 Dec 15, 2022
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees

ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica

Kuan-Lin (Jason) Chen 2 Oct 02, 2022
Coarse implement of the paper "A Simultaneous Denoising and Dereverberation Framework with Target Decoupling", On DNS-2020 dataset, the DNSMOS of first stage is 3.42 and second stage is 3.47.

SDDNet Coarse implement of the paper "A Simultaneous Denoising and Dereverberation Framework with Target Decoupling", On DNS-2020 dataset, the DNSMOS

Cyril Lv 43 Nov 21, 2022
Checkout some cool self-projects you can try your hands on to curb your boredom this December!

SoC-Winter Checkout some cool self-projects you can try your hands on to curb your boredom this December! These are short projects that you can do you

Web and Coding Club, IIT Bombay 29 Nov 08, 2022
All the code and files related to the MI-Lab of UE19CS305 course in sem 5

Machine-Intelligence-Lab-CS305 The compilation of all the code an drelated files from MI-Lab UE19CS305 (of batch 2019-2023) offered by PES University

Arvind Krishna 3 Nov 10, 2022
yolox_backbone is a deep-learning library and is a collection of YOLOX Backbone models.

YOLOX-Backbone yolox-backbone is a deep-learning library and is a collection of YOLOX backbone models. Install pip install yolox-backbone Load a Pret

Yonghye Kwon 21 Dec 28, 2022
Machine Translation Implement By Bi-GRU And Transformer

Seq2Seq Translation Implement By Bidirectional GRU And Transformer In Pytorch Before You Run The Code You should download the data through the link be

He Wang 2 Oct 27, 2021
Tensorflow implementation for Self-supervised Graph Learning for Recommendation

If the compilation is successful, the evaluator of cpp implementation will be called automatically. Otherwise, the evaluator of python implementation will be called.

152 Jan 07, 2023