377 Repositories
Python stroke-prediction Libraries
Fast and scalable uncertainty quantification for neural molecular property prediction, accelerated optimization, and guided virtual screening.
Evidential Deep Learning for Guided Molecular Property Prediction and Discovery Ava Soleimany*, Alexander Amini*, Samuel Goldman*, Daniela Rus, Sangee
Joint parameterization and fitting of stroke clusters
StrokeStrip: Joint Parameterization and Fitting of Stroke Clusters Dave Pagurek van Mossel1, Chenxi Liu1, Nicholas Vining1,2, Mikhail Bessmeltsev3, Al
Implementation of "A MLP-like Architecture for Dense Prediction"
A MLP-like Architecture for Dense Prediction (arXiv) Updates (22/07/2021) Initial release. Model Zoo We provide CycleMLP models pretrained on ImageNet
Pervasive Attention: 2D Convolutional Networks for Sequence-to-Sequence Prediction
This is a fork of Fairseq(-py) with implementations of the following models: Pervasive Attention - 2D Convolutional Neural Networks for Sequence-to-Se
Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax
Clockwork VAEs in JAX/Flax Implementation of experiments in the paper Clockwork Variational Autoencoders (project website) using JAX and Flax, ported
An end-to-end implementation of intent prediction with Metaflow and other cool tools
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
A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK
Pytorch-MBNet A pytorch implementation of MBNET: MOS PREDICTION FOR SYNTHESIZED SPEECH WITH MEAN-BIAS NETWORK Training To train a new model, please ru
MachineLearningStocks is designed to be an intuitive and highly extensible template project applying machine learning to making stock predictions.
Using python and scikit-learn to make stock predictions
🤖 A Python library for learning and evaluating knowledge graph embeddings
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 locomotion (pose + trajectory) prediction (forecasting)
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)
Beyond Image to Depth: Improving Depth Prediction using Echoes (CVPR 2021) Kranti Kumar Parida, Siddharth Srivastava, Gaurav Sharma. We address the pr
This repository is based on Ultralytics/yolov5, with adjustments to enable polygon prediction boxes.
Polygon-Yolov5 This repository is based on Ultralytics/yolov5, with adjustments to enable polygon prediction boxes. Section I. Description The codes a
Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.
Official PyTorch implementation of the preprint paper "Stylized Neural Painting", accepted to CVPR 2021.
pure-predict: Machine learning prediction in pure Python
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.
PyTorch implementation of ARM-Net: Adaptive Relation Modeling Network for Structured Data.
A ready-to-use framework of latest models for structured (tabular) data learning with PyTorch. Applications include recommendation, CRT prediction, healthcare analytics, and etc.
Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network
DeepCDR Cancer Drug Response Prediction via a Hybrid Graph Convolutional Network This work has been accepted to ECCB2020 and was also published in the
Implementation of FitVid video prediction model in JAX/Flax.
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:
A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!
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 based on PyTorch
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.
MolRep: A Deep Representation Learning Library for Molecular Property Prediction
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
Waymo motion prediction challenge 2021: 3rd place solution 📜 Technical report 🗨️ Presentation 🎉 Announcement 🛆Motion Prediction Channel Website 🛆
VIMPAC: Video Pre-Training via Masked Token Prediction and Contrastive Learning
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.
Code for our ACL 2021 paper "One2Set: Generating Diverse Keyphrases as a Set"
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.
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
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.
🔮 Execution time predictions for deep neural network training iterations across different GPUs.
Habitat: A Runtime-Based Computational Performance Predictor for Deep Neural Network Training Habitat is a tool that predicts a deep neural network's
The official code of Anisotropic Stroke Control for Multiple Artists Style Transfer
ASMA-GAN Anisotropic Stroke Control for Multiple Artists Style Transfer Proceedings of the 28th ACM International Conference on Multimedia The officia
SpanNER: Named EntityRe-/Recognition as Span Prediction
SpanNER: Named EntityRe-/Recognition as Span Prediction Overview | Demo | Installation | Preprocessing | Prepare Models | Running | System Combination
Unofficial TensorFlow implementation of Protein Interface Prediction using Graph Convolutional Networks.
[TensorFlow] Protein Interface Prediction using Graph Convolutional Networks Unofficial TensorFlow implementation of Protein Interface Prediction usin
This is the repo for the paper `SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization'. (published in Bioinformatics'21)
SumGNN: Multi-typed Drug Interaction Prediction via Efficient Knowledge Graph Summarization This is the code for our paper ``SumGNN: Multi-typed Drug
A Python Module That Uses ANN To Predict A Stocks Price And Also Provides Accurate Technical Analysis With Many High Potential Implementations!
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
TANL: Structured Prediction as Translation between Augmented Natural Languages
TANL: Structured Prediction as Translation between Augmented Natural Languages Code for the paper "Structured Prediction as Translation between Augmen
Fast, general, and tested differentiable structured prediction in PyTorch
Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic
Code and datasets for the paper "Combining Events and Frames using Recurrent Asynchronous Multimodal Networks for Monocular Depth Prediction" (RA-L, 2021)
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.
AdelaiDepth is an open source toolbox for monocular depth prediction.
Structural basis for solubility in protein expression systems
Structural basis for solubility in protein expression systems Large-scale protein production for biotechnology and biopharmaceutical applications rely
A scikit-learn-compatible module for estimating prediction intervals.
|Anaconda|_ MAPIE - Model Agnostic Prediction Interval Estimator MAPIE allows you to easily estimate prediction intervals using your favourite sklearn
TalkNet 2: Non-Autoregressive Depth-Wise Separable Convolutional Model for Speech Synthesis with Explicit Pitch and Duration Prediction.
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
Few-shot Graph Learning for Molecular Property Prediction Introduction This is the source code and dataset for the following paper: Few-shot Graph Lea
A Plover python dictionary allowing for consistent symbol input with specification of attachment and capitalisation in one stroke.
Emily's Symbol Dictionary Design This dictionary was created with the following goals in mind: Have a consistent method to type (pretty much) every sy
:boar: :bear: Deep Learning based Python Library for Stock Market Prediction and Modelling
bulbea "Deep Learning based Python Library for Stock Market Prediction and Modelling." Table of Contents Installation Usage Documentation Dependencies
Use deep learning, genetic programming and other methods to predict stock and market movements
StockPredictions Use classic tricks, neural networks, deep learning, genetic programming and other methods to predict stock and market movements. Both
OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network
Stock Price Prediction of Apple Inc. Using Recurrent Neural Network OHLC Average Prediction of Apple Inc. Using LSTM Recurrent Neural Network Dataset:
Introducing neural networks to predict stock prices
IntroNeuralNetworks in Python: A Template Project IntroNeuralNetworks is a project that introduces neural networks and illustrates an example of how o
Use unsupervised and supervised learning to predict stocks
AIAlpha: Multilayer neural network architecture for stock return prediction This project is meant to be an advanced implementation of stacked neural n
Using python and scikit-learn to make stock predictions
MachineLearningStocks in python: a starter project and guide EDIT as of Feb 2021: MachineLearningStocks is no longer actively maintained MachineLearni
Official implementation for NIPS'17 paper: PredRNN: Recurrent Neural Networks for Predictive Learning Using Spatiotemporal LSTMs.
PredRNN: A Recurrent Neural Network for Spatiotemporal Predictive Learning The predictive learning of spatiotemporal sequences aims to generate future
PyTorch implementation for COMPLETER: Incomplete Multi-view Clustering via Contrastive Prediction (CVPR 2021)
Completer: Incomplete Multi-view Clustering via Contrastive Prediction This repo contains the code and data of the following paper accepted by CVPR 20
git《Joint Entity and Relation Extraction with Set Prediction Networks》(2020) GitHub:
Joint Entity and Relation Extraction with Set Prediction Networks Source code for Joint Entity and Relation Extraction with Set Prediction Networks. W
Code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction
Official PyTorch code for Transformers Solve Limited Receptive Field for Monocular Depth Prediction. Guanglei Yang, Hao Tang, Mingli Ding, Nicu Sebe,
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
A Python library for dynamic classifier and ensemble selection
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
Fast, general, and tested differentiable structured prediction in PyTorch
Torch-Struct: Structured Prediction Library A library of tested, GPU implementations of core structured prediction algorithms for deep learning applic
Probabilistic time series modeling in Python
GluonTS - Probabilistic Time Series Modeling in Python GluonTS is a Python toolkit for probabilistic time series modeling, built around Apache MXNet (
[arXiv] What-If Motion Prediction for Autonomous Driving ❓🚗💨
WIMP - What If Motion Predictor Reference PyTorch Implementation for What If Motion Prediction [PDF] [Dynamic Visualizations] Setup Requirements The W
[ECCVW2020] Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DiMP)
Feel free to visit my homepage Robust Long-Term Object Tracking via Improved Discriminative Model Prediction (RLT-DIMP) [ECCVW2020 paper] Presentation
[ICML 2020] Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Control
PG-MORL This repository contains the implementation for the paper Prediction-Guided Multi-Objective Reinforcement Learning for Continuous Robot Contro
Dense Prediction Transformers
Vision Transformers for Dense Prediction This repository contains code and models for our paper: Vision Transformers for Dense Prediction René Ranftl,
Linear Prediction Coefficients estimation from mel-spectrogram implemented in Python based on Levinson-Durbin algorithm.
LPC_for_TTS Linear Prediction Coefficients estimation from mel-spectrogram implemented in Python based on Levinson-Durbin algorithm. 基于Levinson-Durbin
Monocular Depth Estimation - Weighted-average prediction from multiple pre-trained depth estimation models
merged_depth runs (1) AdaBins, (2) DiverseDepth, (3) MiDaS, (4) SGDepth, and (5) Monodepth2, and calculates a weighted-average per-pixel absolute dept
Lightning Fast Language Prediction 🚀
whatthelang Lightning Fast Language Prediction 🚀 Dependencies The dependencies can be installed using the requirements.txt file: $ pip install -r req
[CIKM 2019] Code and dataset for "Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction"
FiGNN for CTR prediction The code and data for our paper in CIKM2019: Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Predicti
To be a next-generation DL-based phenotype prediction from genome mutations.
Sequence -----------+-- 3D_structure -- 3D_module --+ +-- ? | |
Baselines for TrajNet++
TrajNet++ : The Trajectory Forecasting Framework PyTorch implementation of Human Trajectory Forecasting in Crowds: A Deep Learning Perspective TrajNet
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction
FLAVR is a fast, flow-free frame interpolation method capable of single shot multi-frame prediction. It uses a customized encoder decoder architecture with spatio-temporal convolutions and channel gating to capture and interpolate complex motion trajectories between frames to generate realistic high frame rate videos. This repository contains original source code for the paper accepted to CVPR 2021.
Supervised domain-agnostic prediction framework for probabilistic modelling
A supervised domain-agnostic framework that allows for probabilistic modelling, namely the prediction of probability distributions for individual data
FairML - is a python toolbox auditing the machine learning models for bias.
======== FairML: Auditing Black-Box Predictive Models FairML is a python toolbox auditing the machine learning models for bias. Description Predictive
Stacked Generalization (Ensemble Learning)
Stacking (stacked generalization) Overview ikki407/stacking - Simple and useful stacking library, written in Python. User can use models of scikit-lea
MLBox is a powerful Automated Machine Learning python library.
MLBox is a powerful Automated Machine Learning python library. It provides the following features: Fast reading and distributed data preprocessing/cle
A scikit-learn based module for multi-label et. al. classification
scikit-multilearn scikit-multilearn is a Python module capable of performing multi-label learning tasks. It is built on-top of various scientific Pyth
The 3rd place solution for competition
The 3rd place solution for competition "Lyft Motion Prediction for Autonomous Vehicles" at Kaggle Team behind this solution: Artsiom Sanakoyeu [Homepa
Age and Gender prediction using Keras
cnn_age_gender Age and Gender prediction using Keras Dataset example : Description : UTKFace dataset is a large-scale face dataset with long age span
Kaggle Lyft Motion Prediction for Autonomous Vehicles 4th place solution
Lyft Motion Prediction for Autonomous Vehicles Code for the 4th place solution of Lyft Motion Prediction for Autonomous Vehicles on Kaggle. Discussion
An end-to-end machine learning web app to predict rugby scores (Pandas, SQLite, Keras, Flask, Docker)
Rugby score prediction An end-to-end machine learning web app to predict rugby scores Overview An demo project to provide a high-level overview of the
The windML framework provides an easy-to-use access to wind data sources within the Python world, building upon numpy, scipy, sklearn, and matplotlib. Renewable Wind Energy, Forecasting, Prediction
windml Build status : The importance of wind in smart grids with a large number of renewable energy resources is increasing. With the growing infrastr
Model Serving Made Easy
The easiest way to build Machine Learning APIs BentoML makes moving trained ML models to production easy: Package models trained with any ML framework
StellarGraph - Machine Learning on Graphs
StellarGraph Machine Learning Library StellarGraph is a Python library for machine learning on graphs and networks. Table of Contents Introduction Get