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
A collection of IPython notebooks covering various topics.
ipython-notebooks This repo contains various IPython notebooks I've created to experiment with libraries and work through exercises, and explore subje
2.6k Jan 01, 2023
PyTorch implementations of the paper: "DR.VIC: Decomposition and Reasoning for Video Individual Counting, CVPR, 2022"
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Submanifold sparse convolutional networks
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KeypointDeformer: Unsupervised 3D Keypoint Discovery for Shape Control
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An alarm clock coded in Python 3 with Tkinter
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Using a Seq2Seq RNN architecture via TensorFlow to predict future Bitcoin prices
Recurrent Bitcoin Network A Data Science Thesis Project About This repository contains the source code for implementing Bitcoin price prediciton using
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Do you like Quick, Draw? Well what if you could train/predict doodles drawn inside Streamlit? Also draws lines, circles and boxes over background images for annotation.
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325 Dec 28, 2022
Breaking the Curse of Space Explosion: Towards Efficient NAS with Curriculum Search
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Exploration-Exploitation Dilemma Solving Methods
Exploration-Exploitation Dilemma Solving Methods Medium article for this repo - HERE In ths repo I implemented two techniques for tackling mentioned t
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A Novel Plug-in Module for Fine-grained Visual Classification
Pytorch implementation for A Novel Plug-in Module for Fine-Grained Visual Classification. fine-grained visual classification task.
109 Dec 20, 2022
This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murder rates etc.
Gun-Laws-Classifier This is a classifier which basically predicts whether there is a gun law in a state or not, depending on various things like murde
1 Jan 20, 2022
Official implementations of PSENet, PAN and PAN++.
News (2021/11/03) Paddle implementation of PAN, see Paddle-PANet. Thanks @simplify23. (2021/04/08) PSENet and PAN are included in MMOCR. Introduction
395 Dec 14, 2022
A repo that contains all the mesh keys needed for mesh backend, along with a code example of how to use them in python
Mesh-Keys A repo that contains all the mesh keys needed for mesh backend, along with a code example of how to use them in python Have been seeing alot
53 Dec 13, 2022
Code for the CVPR 2021 paper: Understanding Failures of Deep Networks via Robust Feature Extraction
Welcome to Barlow Barlow is a tool for identifying the failure modes for a given neural network. To achieve this, Barlow first creates a group of imag
33 Dec 05, 2022
Code for "FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection", ICRA 2021
FGR This repository contains the python implementation for paper "FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection"(I
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Paaster is a secure by default end-to-end encrypted pastebin built with the objective of simplicity.
Follow the development of our desktop client here Paaster Paaster is a secure by default end-to-end encrypted pastebin built with the objective of sim
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《Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching》(CVPR 2020)
This contains the codes for cross-view geo-localization method described in: Where am I looking at? Joint Location and Orientation Estimation by Cross-View Matching, CVPR2020.
41 Oct 27, 2022
Code accompanying the NeurIPS 2021 paper "Generating High-Quality Explanations for Navigation in Partially-Revealed Environments"
Generating High-Quality Explanations for Navigation in Partially-Revealed Environments This work presents an approach to explainable navigation under
1 Oct 28, 2022
Code & Models for Temporal Segment Networks (TSN) in ECCV 2016
Temporal Segment Networks (TSN) We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation fo
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Official Implementation of "Transformers Can Do Bayesian Inference"
Official Code for the Paper "Transformers Can Do Bayesian Inference" We train Transformers to do Bayesian Prediction on novel datasets for a large var
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