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This is a PyTorch reimplementation of Influence Functions from the ICML2017 best paper: Understanding Black-box Predictions via Influence Functions by Pang Wei Koh and Percy Liang.
CLIP (Contrastive Language-Image Pretraining), Predict the most relevant text snippet given an image
A toolbox to iNNvestigate neural networks' predictions!
Systematic Evaluation of Membership Inference Privacy Risks of Machine Learning Models
BSC5P Star Catalogue converted to JSON format
Privacy Meter: An open-source library to audit data privacy in statistical and machine learning algorithms.
A Python toolbox to create adversarial examples that fool neural networks in PyTorch, TensorFlow, and JAX
An adversarial example library for constructing attacks, building defenses, and benchmarking both
Osintgram is a OSINT tool on Instagram. It offers an interactive shell to perform analysis on Instagram account of any users by its nickname
Performance metrics for semi-supervised classification
A 360° media viewer for the modern web.
Code for visualizing the loss landscape of neural nets
It is demonstration tool that contains collection techniques to detect the virtualisation environment in Linux Operating System.
Public malware techniques used in the wild: Virtual Machine, Emulation, Debuggers, Sandbox detection.
A work-in-progress chess bot written in C#
Blender addons to make the bridge between Blender and geographic data
The 1st Place Solution of the Google Landmark 2019 Retrieval Challenge and the 3rd Place Solution of the Recognition Challenge.
Dataset with 5 million images depicting human-made and natural landmarks spanning 200 thousand classes.
This repository contains the source code for the paper First Order Motion Model for Image Animation
Faster R-CNN (Python implementation) -- see https://github.com/ShaoqingRen/faster_rcnn for the official MATLAB version
Use Facebook to track your friends’ sleeping habits
Deezer source separation library including pretrained models.
Tensorflow Demo for my TF in 5 Min Video on Youtube
Code and data for paper "Deep Photo Style Transfer": https://arxiv.org/abs/1703.07511