fake-news-explainability
Experiments for fake news explainability project
This repository only contains the notebooks used to train the models and evaluate them. The data and models can be found here:
Experiments for Fake News explainability project
Overview
Restricted Boltzmann Machines in Python.
How to Use First, initialize an RBM with the desired number of visible and hidden units. rbm = RBM(num_visible = 6, num_hidden = 2) Next, train the m
928 Dec 30, 2022
Using machine learning to predict and analyze high and low reader engagement for New York Times articles posted to Facebook.
How The New York Times can increase Engagement on Facebook Using machine learning to understand characteristics of news content that garners "high" Fa
0 Sep 16, 2021
Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021).
AA-RMVSNet Code for AA-RMVSNet: Adaptive Aggregation Recurrent Multi-view Stereo Network (ICCV 2021) in PyTorch. paper link: arXiv | CVF Change Log Ju
97 Dec 30, 2022
Large scale PTM - PPI relation extraction
Large-scale protein-protein post-translational modification extraction with distant supervision and confidence calibrated BioBERT The silver standard
1 Feb 25, 2022
Lacmus is a cross-platform application that helps to find people who are lost in the forest using computer vision and neural networks.
lacmus The program for searching through photos from the air of lost people in the forest using Retina Net neural nwtwork. The project is being develo
168 Dec 27, 2022
SafePicking: Learning Safe Object Extraction via Object-Level Mapping, ICRA 2022
SafePicking Learning Safe Object Extraction via Object-Level Mapping Kentaro Wad
49 Oct 24, 2022
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics.
Bonnet: An Open-Source Training and Deployment Framework for Semantic Segmentation in Robotics. By Andres Milioto @ University of Bonn. (for the new P
314 Dec 30, 2022
Human4D Dataset tools for processing and visualization
HUMAN4D: A Human-Centric Multimodal Dataset for Motions & Immersive Media HUMAN4D constitutes a large and multimodal 4D dataset that contains a variet
15 Nov 09, 2022
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings
When Does Pretraining Help? Assessing Self-Supervised Learning for Law and the CaseHOLD Dataset of 53,000+ Legal Holdings This is the repository for t
39 Jan 07, 2023
Pytorch implementation for Semantic Segmentation/Scene Parsing on MIT ADE20K dataset
Semantic Segmentation on MIT ADE20K dataset in PyTorch This is a PyTorch implementation of semantic segmentation models on MIT ADE20K scene parsing da
4.5k Jan 08, 2023
This is the official PyTorch implementation of the paper "TransFG: A Transformer Architecture for Fine-grained Recognition" (Ju He, Jie-Neng Chen, Shuai Liu, Adam Kortylewski, Cheng Yang, Yutong Bai, Changhu Wang, Alan Yuille).
TransFG: A Transformer Architecture for Fine-grained Recognition Official PyTorch code for the paper: TransFG: A Transformer Architecture for Fine-gra
307 Jan 03, 2023
rliable is an open-source Python library for reliable evaluation, even with a handful of runs, on reinforcement learning and machine learnings benchmarks.
Open-source library for reliable evaluation on reinforcement learning and machine learning benchmarks. See NeurIPS 2021 oral for details.
529 Jan 01, 2023
Fuwa-http - The http client implementation for the fuwa eco-system
Fuwa HTTP The HTTP client implementation for the fuwa eco-system Example import
2 Feb 16, 2022
Pytorch implementation of SimSiam Architecture
SimSiam-pytorch A simple pytorch implementation of Exploring Simple Siamese Representation Learning which is developed by Facebook AI Research (FAIR)
1 Oct 20, 2021
Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch
CoCa - Pytorch Implementation of CoCa, Contrastive Captioners are Image-Text Foundation Models, in Pytorch. They were able to elegantly fit in contras
565 Dec 30, 2022
PyTorch Implementation of SSTNs for hyperspectral image classifications from the IEEE T-GRS paper "Spectral-Spatial Transformer Network for Hyperspectral Image Classification: A FAS Framework."
PyTorch Implementation of SSTN for Hyperspectral Image Classification Paper links: SSTN published on IEEE T-GRS. Also, you can directly find the imple
54 Dec 19, 2022
A Pytorch Implementation of [Source data‐free domain adaptation of object detector through domain
A Pytorch Implementation of Source data‐free domain adaptation of object detector through domain‐specific perturbation Please follow Faster R-CNN and
1 Dec 25, 2021
PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020).
Scaffold-Federated-Learning PyTorch implementation of SCAFFOLD (Stochastic Controlled Averaging for Federated Learning, ICML 2020). Environment numpy=
30 Dec 29, 2022
StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN
StyleGAN of All Trades: Image Manipulation withOnly Pretrained StyleGAN This is the PyTorch implementation of StyleGAN of All Trades: Image Manipulati
360 Dec 28, 2022
AI-Bot - 一个基于watermelon改造的OpenAI-GPT-2的智能机器人
AI-Bot 一个基于watermelon改造的OpenAI-GPT-2的智能机器人 在Binder上直接运行测试 目前有两种实现方式 TF2的GPT-2 TF
9 Nov 16, 2022