Python Traffic-flow-prediction Resources

Hierarchical Conditional Flow: A Unified Framework for Image Super-Resolution and Image Rescaling (HCFlow, ICCV2021) This repository is the official P

VAE with Volume-Preserving Flows This is a PyTorch implementation of two volume-preserving flows as described in the following papers: Tomczak, J. M.,

Rotate-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable rotate prediction boxes. Section I. Description The codes are

Microsoft365_devicePhish Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack This is a simple proof-of-concept script that allows an at

Torch-RGCN Torch-RGCN is a PyTorch implementation of the RGCN, originally proposed by Schlichtkrull et al. in Modeling Relational Data with Graph Conv

Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation Implementation for our paper, submitted to NeurIPS 2021 (also chec

High-Resolution Transformer for Dense Prediction Introduction This is the official implementation of High-Resolution Transformer (HRT). We present a H

Malcolm is a powerful, easily deployable network traffic analysis tool suite for full packet capture artifacts (PCAP files) and Zeek logs.

Microsoft365_devicePhish Abusing Microsoft 365 OAuth Authorization Flow for Phishing Attack This is a simple proof-of-concept script that allows an at

It is expected to develop a machine learning model that can predict customers who will leave the company.

LOC-FLOW is an “hands-free” earthquake location workflow to process continuous seismic records: from raw waveforms to well located earthquakes with magnitude calculations. The package assembles several popular routines for sequential earthquake location refinements, suitable for catalog building ranging from local to regional scales.

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

Note: This is an alpha (preview) version which is still under refining. nn-Meter is a novel and efficient system to accurately predict the inference l

Paint Transformer: Feed Forward Neural Painting with Stroke Prediction [Paper] [PaddlePaddle Implementation] Homepage of paper: Paint Transformer: Fee

VideoBERT This repo reproduces the results of VideoBERT (https://arxiv.org/pdf/1904.01766.pdf). Inspiration was taken from https://github.com/MDSKUL/M

How to Become More Salient? Surfacing Representation Biases of the Saliency Prediction Model

PyTorch Lightning Optical Flow models, scripts, and pretrained weights.

Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network

snappi-trex snappi-trex is a snappi plugin that allows executing scripts written using snappi with Cisco's TRex Traffic Generator Design snappi-trex c

Panoptic Segmentation Forecasting Colin Graber, Grace Tsai, Michael Firman, Gabriel Brostow, Alexander Schwing - CVPR 2021 [Link to paper] We propose

Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,

Trajectory Prediction using Equivariant Continuous Convolution (ECCO) This is the codebase for the ICLR 2021 paper Trajectory Prediction using Equivar

Inductive entity representations from text via link prediction This repository contains the code used for the experiments in the paper "Inductive enti

ParallelFold Author: Bozitao Zhong This is a modified version of DeepMind's Alphafold2 to divide CPU part (MSA and template searching) and GPU part (p

RIFE RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation Ported from https://github.com/hzwer/arXiv2020-RIFE Dependencies NumPy

flownet2-pytorch Pytorch implementation of FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks. Multiple GPU training is supported, a

Implementation of Deep-Forecast using PyTorch Deep Forecast: Deep Learning-based Spatio-Temporal Forecasting Adapted from original implementation Setu

Visual-Interaction-Networks An implementation of Deepmind visual interaction networks in Pytorch. Introduction For the purpose of understanding the ch

Deep Learning for Physical Processes: Integrating Prior Scientific Knowledge: Official Pytorch implementation of ICLR 2018 paper Deep Learning for Phy

LogDeep is an open source deeplearning-based log analysis toolkit for automated anomaly detection.

A curated list of amazingly awesome Cybersecurity datasets

GNN4Traffic - This is the repository for the collection of Graph Neural Network for Traffic Forecasting

Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee

A MLP-like Architecture for Dense Prediction (arXiv) Updates (22/07/2021) Initial release. Model Zoo We provide CycleMLP models pretrained on ImageNet

This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se

WaveGlow: a Flow-based Generative Network for Speech Synthesis Ryan Prenger, Rafael Valle, and Bryan Catanzaro In our recent paper, we propose WaveGlo

WaveGlow A PyTorch implementation of the WaveGlow: A Flow-based Generative Network for Speech Synthesis Quick Start: Install requirements: pip install

This is a Pytorch implementation of Janai, J., Güney, F., Ranjan, A., Black, M. and Geiger, A., Unsupervised Learning of Multi-Frame Optical Flow with

Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported

You Don't Need a Bigger Boat An end-to-end (Metaflow-based) implementation of an intent prediction flow for kids who can't MLOps good and wanna learn

Pytorch-MBNet A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK Training To train a new model, please ru

Using python and scikit-learn to make stock predictions

Dewarping Document Image By Displacement Flow Estimation with Fully Convolutional Network

glow-pytorch PyTorch implementation of Glow, Generative Flow with Invertible 1x1 Convolutions

PyKEEN PyKEEN (Python KnowlEdge EmbeddiNgs) is a Python package designed to train and evaluate knowledge graph embedding models (incorporating multi-m

A selection of State Of The Art research papers (and code) on human trajectory prediction (forecasting). Papers marked with [W] are workshop papers.

Beyond Image to Depth: Improving Depth Prediction using Echoes (CVPR 2021) Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma. We address the pr

Polygon-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable polygon prediction boxes. Section I. Description The codes a

Box is a text-based visual programming language inspired by Unreal Engine blueprint function graphs. $ cat factorial.box ┌─ƒ(Factorial)───┐

pure-predict speeds up and slims down machine learning prediction applications. It is a foundational tool for serverless inference or small batch prediction with popular machine learning frameworks like scikit-learn and fasttext. It implements the predict methods of these frameworks in pure Python.

ARTIF is a new advanced real time threat intelligence framework built that adds another abstraction layer on the top of MISP to identify threats and malicious web traffic on the basis of IP reputation and historical data. It also performs automatic enrichment and threat scoring by collecting, processing and correlating observables based on different factors.

A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.

DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the

FitVid Video Prediction Model Implementation of FitVid video prediction model in JAX/Flax. If you find this code useful, please cite it in your paper:

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

LibTraffic is a unified, flexible and comprehensive traffic prediction library, which provides researchers with a credibly experimental tool and a convenient development framework. Our library is implemented based on PyTorch, and includes all the necessary steps or components related to traffic prediction into a systematic pipeline.

MODeflattener deobfuscates control flow flattened functions obfuscated by OLLVM using Miasm.

MolRep: A Deep Representation Learning Library for Molecular Property Prediction Summary MolRep is a Python package for fairly measuring algorithmic p

Waymo motion prediction challenge 2021: 3rd place solution 📜 Technical report 🗨️ Presentation 🎉 Announcement 🛆Motion Prediction Channel Website 🛆

This is a release of our VIMPAC paper to illustrate the implementations. The pretrained checkpoints and scripts will be soon open-sourced in HuggingFace transformers.

A collection of modules that I have created to programmatically search for/download imagery from all publicly available live cam feeds across the state of California. In no way am I affiliated with any of these organizations and these modules/methods of gathering imagery are completely unofficial.

One2Set This repository contains the code for our ACL 2021 paper “One2Set: Generating Diverse Keyphrases as a Set”. Our implementation is built on the

Markup is an online annotation tool that can be used to transform unstructured documents into structured formats for NLP and ML tasks, such as named-entity recognition. Markup learns as you annotate in order to predict and suggest complex annotations. Markup also provides integrated access to existing and custom ontologies, enabling the prediction and suggestion of ontology mappings based on the text you're annotating.

We envision models that are pre-trained on a vast range of domain-relevant tasks to become key for molecule property prediction. This repository aims to give easy access to state-of-the-art pre-trained models.

Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's

FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation The official PyTorch implementation of FastFlowNet (ICRA 2021). Authors: Lingtong

Learning Optical Flow from a Few Matches This repository contains the source code for our paper: Learning Optical Flow from a Few Matches CVPR 2021 Sh

SpanNER: Named EntityRe-/Recognition as Span Prediction Overview | Demo | Installation | Preprocessing | Prepare Models | Running | System Combination

[TensorFlow] Protein Interface Prediction using Graph Convolutional Networks Unofficial TensorFlow implementation of Protein Interface Prediction usin

MaskFlownet-Pytorch Unofficial PyTorch implementation of MaskFlownet (https://github.com/microsoft/MaskFlownet). Tested with: PyTorch 1.5.0 CUDA 10.1

SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug

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

Flow-to-depth (FDNet) video-depth-estimation This is the implementation of paper Video Depth Estimation by Fusing Flow-to-Depth Proposals Jiaxin Xie,

PV-RAFT This repository contains the PyTorch implementation for paper "PV-RAFT: Point-Voxel Correlation Fields for Scene Flow Estimation of Point Clou

Conversations are not Flat: Modeling the Intrinsic Information Flow between Dialogue Utterances This repository contains the code and pre-trained mode

TANL: Structured Prediction as Translation between Augmented Natural Languages Code for the paper "Structured Prediction as Translation between Augmen

Self-Supervised Multi-Frame Monocular Scene Flow 3D visualization of estimated depth and scene flow (overlayed with input image) from temporally conse

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction This is the code for the paper Combining E

AdelaiDepth is an open source toolbox for monocular depth prediction.

Structural basis for solubility in protein expression systems Large-scale protein production for biotechnology and biopharmaceutical applications rely

|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn

Just Go with the Flow: Self-Supervised Scene Flow Estimation Code release for the paper Just Go with the Flow: Self-Supervised Scene Flow Estimation,

TalkNet 2 [WIP] TalkNet 2: Non-Autoregressive Depth-Wise Separable Convolutional Model for Speech Synthesis with Explicit Pitch and Duration Predictio

Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea

bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies

StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both

Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:

IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o

AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n

MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni

Depthstillation Demo code for "Learning optical flow from still images", CVPR 2021. [Project page] - [Paper] - [Supplementary] This code is provided t

PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future

Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20

Joint Entity and Relation Extraction with Set Prediction Networks Source code for Joint Entity and Relation Extraction with Set Prediction Networks. W

Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,

scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth

DESlib DESlib is an easy-to-use ensemble learning library focused on the implementation of the state-of-the-art techniques for dynamic classifier and

Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic

GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (