Python Potential Resources

Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md

SharkTankInvestor This is the data scrapped of all the pitches made up potential startup's to established bussiness tycoons of India with all the deta

Validate arbitrary base64-encoded image uploads as incoming data urls while preserving image integrity but removing EXIF and unwanted artifacts and mitigating RCE-exploit potential.

Showing potential issues with merge strategies Context There are two branches in this repo: main and a feature branch feat/inverting-method (not the b

Fuzz introspector Fuzz introspector is a tool to help fuzzer developers to get an understanding of their fuzzer’s performance and identify any potenti

The following people contributed equally to this repository (in alphabetical order): Daniel Bumke JJX Corstiaen Versteegh This repository is forked on

Make Complex Heatmaps Complex heatmaps are efficient to visualize associations between different sources of data sets and reveal potential patterns. H

nsff_pl Neural Scene Flow Fields using pytorch-lightning. This repo reimplements the NSFF idea, but modifies several operations based on observation o

DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc

Dependency Combobulator Dependency Combobulator is an Open-Source, modular and extensible framework to detect and prevent dependency confusion leakage

Moiré Attack (MA): A New Potential Risk of Screen Photos [NeurIPS 2021] This repository is the official implementation of Moiré Attack (MA): A New Pot

DAS Dual Adaptive Sampling for Machine Learning Interatomic potential. How to cite If you use this code in your research, please cite this using: Hong

EPCDepth EPCDepth is a self-supervised monocular depth estimation model, whose supervision is coming from the other image in a stereo pair. Details ar

Table of Contents Table of Contents Local Planner Visualization Project (LPVP) Features Installation/Usage Local Planners Probabilistic Roadmap (PRM)

Graph Transformer - Pytorch Implementation of Graph Transformer in Pytorch, for potential use in replicating Alphafold2. This was recently used by bot

Stox ⚡ A Python Module For The Stock Market ⚡ A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural N

Modeling distributions on Riemannian manifolds is a crucial component in understanding non-Euclidean data that arises, e.g., in physics and geology. The budding approaches in this space are limited by representational and computational tradeoffs. We propose and study a class of flows that uses convex potentials from Riemannian optimal transport. These are universal and can model distributions on any compact Riemannian manifold without requiring domain knowledge of the manifold to be integrated into the architecture. We demonstrate that these flows can model standard distributions on spheres, and tori, on synthetic and geological data.

Stox A Module to predict the "close price" for the next day and give "technical analysis". It uses a Neural Network and the LSTM algorithm to predict

Profil3r is an OSINT tool that allows you to find potential profiles of a person on social networks, as well as their email addresses. This program also alerts you to the presence of a data leak for the found emails.

Description Using hotel data and AI to predict high value guests and potential VIP guests. Hotel can leverage on prediction resutls to run more effect

Contact Potential Field This repo contains model, demo, and test codes of our paper: CPF: Learning a Contact Potential Field to Model the Hand-object

Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technol

Differentiable molecular simulation of proteins with a coarse-grained potential This repository contains the learned potential, simulation scripts and