1390 Repositories
Python structural-causal-model Libraries
Stochastic gradient descent with model building
Stochastic Model Building (SMB) This repository includes a new fast and robust stochastic optimization algorithm for training deep learning models. Th
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization
Iterative Training: Finding Binary Weight Deep Neural Networks with Layer Binarization This repository contains the source code for the paper (link wi
⚖️🔁🔮🕵️♂️🦹🖼️ Code for *Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances* paper.
Measuring the Contribution of Multiple Model Representations in Detecting Adversarial Instances This repository contains the code for Measuring the Co
Code and real data for the paper "Counterfactual Temporal Point Processes", available at arXiv.
counterfactual-tpp This is a repository containing code and real data for the paper Counterfactual Temporal Point Processes. Pre-requisites This code
Official code for: A Probabilistic Hard Attention Model For Sequentially Observed Scenes
"A Probabilistic Hard Attention Model For Sequentially Observed Scenes" Authors: Samrudhdhi Rangrej, James Clark Accepted to: BMVC'21 A recurrent atte
On Effective Scheduling of Model-based Reinforcement Learning
On Effective Scheduling of Model-based Reinforcement Learning Code to reproduce the experiments in On Effective Scheduling of Model-based Reinforcemen
KAPAO is an efficient multi-person human pose estimation model that detects keypoints and poses as objects and fuses the detections to predict human poses.
KAPAO (Keypoints and Poses as Objects) KAPAO is an efficient single-stage multi-person human pose estimation model that models keypoints and poses as
Extracting knowledge graphs from language models as a diagnostic benchmark of model performance.
Interpreting Language Models Through Knowledge Graph Extraction Idea: How do we interpret what a language model learns at various stages of training?
Source code for our EMNLP'21 paper 《Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning》
Child-Tuning Source code for EMNLP 2021 Long paper: Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning. 1. Environ
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning
TaCL: Improving BERT Pre-training with Token-aware Contrastive Learning Authors: Yixuan Su, Fangyu Liu, Zaiqiao Meng, Lei Shu, Ehsan Shareghi, and Nig
glTF to 3d Tiles Converter. Convert glTF model to Glb, b3dm or 3d tiles format.
gltf-to-3d-tiles glTF to 3d Tiles Converter. Convert glTF model to Glb, b3dm or 3d tiles format. Usage λ python main.py --help Usage: main.py [OPTION
Time Series Cross-Validation -- an extension for scikit-learn
TSCV: Time Series Cross-Validation This repository is a scikit-learn extension for time series cross-validation. It introduces gaps between the traini
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions.
Convoys is a simple library that fits a few statistical model useful for modeling time-lagged conversions. There is a lot more info if you head over to the documentation. You can also take a look at this blog post about Convoys.
Python package for causal inference using Bayesian structural time-series models.
Python Causal Impact Causal inference using Bayesian structural time-series models. This package aims at defining a python equivalent of the R CausalI
A Python package for modular causal inference analysis and model evaluations
Causal Inference 360 A Python package for inferring causal effects from observational data. Description Causal inference analysis enables estimating t
DoWhy is a Python library for causal inference that supports explicit modeling and testing of causal assumptions. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.
DoWhy | An end-to-end library for causal inference Amit Sharma, Emre Kiciman Introducing DoWhy and the 4 steps of causal inference | Microsoft Researc
moDel Agnostic Language for Exploration and eXplanation
moDel Agnostic Language for Exploration and eXplanation Overview Unverified black box model is the path to the failure. Opaqueness leads to distrust.
An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning.
NNI Doc | 简体中文 NNI (Neural Network Intelligence) is a lightweight but powerful toolkit to help users automate Feature Engineering, Neural Architecture
Provide an input CSV and a target field to predict, generate a model + code to run it.
automl-gs Give an input CSV file and a target field you want to predict to automl-gs, and get a trained high-performing machine learning or deep learn
ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments.
ModelChimp What is ModelChimp? ModelChimp is an experiment tracker for Deep Learning and Machine Learning experiments. ModelChimp provides the followi
BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models.
Model Serving Made Easy BentoML is a flexible, high-performance framework for serving, managing, and deploying machine learning models. Supports multi
Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects
Metaflow Metaflow is a human-friendly Python/R library that helps scientists and engineers build and manage real-life data science projects. Metaflow
YOLOX_AUDIO is an audio event detection model based on YOLOX
YOLOX_AUDIO is an audio event detection model based on YOLOX, an anchor-free version of YOLO. This repo is an implementated by PyTorch. Main goal of YOLOX_AUDIO is to detect and classify pre-defined audio events in multi-spectrogram domain using image object detection frameworks.
Use of Attention Gates in a Convolutional Neural Network / Medical Image Classification and Segmentation
Attention Gated Networks (Image Classification & Segmentation) Pytorch implementation of attention gates used in U-Net and VGG-16 models. The framewor
A Kitti Road Segmentation model implemented in tensorflow.
KittiSeg KittiSeg performs segmentation of roads by utilizing an FCN based model. The model achieved first place on the Kitti Road Detection Benchmark
SegNet model implemented using keras framework
keras-segnet Implementation of SegNet-like architecture using keras. Current version doesn't support index transferring proposed in SegNet article, so
UNet model with VGG11 encoder pre-trained on Kaggle Carvana dataset
TernausNet: U-Net with VGG11 Encoder Pre-Trained on ImageNet for Image Segmentation By Vladimir Iglovikov and Alexey Shvets Introduction TernausNet is
PyQT5 app that colorize black & white pictures using CNN(use pre-trained model which was made with OpenCV)
About PyQT5 app that colorize black & white pictures using CNN(use pre-trained model which was made with OpenCV) Colorizor Приложение для проекта Yand
causal-learn: Causal Discovery for Python
causal-learn: Causal Discovery for Python Causal-learn is a python package for causal discovery that implements both classical and state-of-the-art ca
KakaoBrain KoGPT (Korean Generative Pre-trained Transformer)
KoGPT KoGPT (Korean Generative Pre-trained Transformer) https://github.com/kakaobrain/kogpt https://huggingface.co/kakaobrain/kogpt Model Descriptions
Blazing fast language detection using fastText model
Luga A blazing fast language detection using fastText's language models Luga is a Swahili word for language. fastText provides a blazing fast language
Understanding the Generalization Benefit of Model Invariance from a Data Perspective
Understanding the Generalization Benefit of Model Invariance from a Data Perspective This is the code for our NeurIPS2021 paper "Understanding the Gen
A Pytorch implementation of MoveNet from Google. Include training code and pre-train model.
Movenet.Pytorch Intro MoveNet is an ultra fast and accurate model that detects 17 keypoints of a body. This is A Pytorch implementation of MoveNet fro
Object detection using yolo-tiny model and opencv used as backend
Object detection Algorithm used : Yolo algorithm Backend : opencv Library required: opencv = 4.5.4-dev' Quick Overview about structure 1) main.py Load
aMLP Transformer Model for Japanese
aMLP-japanese Japanese aMLP Pretrained Model aMLPとは、Liu, Daiらが提案する、Transformerモデルです。 ざっくりというと、BERTの代わりに使えて、より性能の良いモデルです。 詳しい解説は、こちらの記事などを参考にしてください。 この
Algorithms for calibrating power grid distribution system models
Distribution System Model Calibration Algorithms The code in this library was developed by Sandia National Laboratories under funding provided by the
Implementation of the state of the art beat-detection, downbeat-detection and tempo-estimation model
The ISMIR 2020 Beat Detection, Downbeat Detection and Tempo Estimation Model Implementation. This is an implementation in TensorFlow to implement the
IMDB film review sentiment classification based on BERT's supervised learning model.
IMDB film review sentiment classification based on BERT's supervised learning model. On the other hand, the model can be extended to other natural language multi-classification tasks.
PyKaldi is a Python scripting layer for the Kaldi speech recognition toolkit.
PyKaldi is a Python scripting layer for the Kaldi speech recognition toolkit. It provides easy-to-use, low-overhead, first-class Python wrappers for t
Generate music from midi files using BPE and markov model
Generate music from midi files using BPE and markov model
Python code for solving 3D structural problems using the finite element method
3DFEM Python 3D finite element code This python code allows for solving 3D structural problems using the finite element method. New features will be a
MIRACLE (Missing data Imputation Refinement And Causal LEarning)
MIRACLE (Missing data Imputation Refinement And Causal LEarning) Code Author: Trent Kyono This repository contains the code used for the "MIRACLE: Cau
State-to-Distribution (STD) Model
State-to-Distribution (STD) Model In this repository we provide exemplary code on how to construct and evaluate a state-to-distribution (STD) model fo
ACV is a python library that provides explanations for any machine learning model or data.
ACV is a python library that provides explanations for any machine learning model or data. It gives local rule-based explanations for any model or data and different Shapley Values for tree-based models.
This repository contains the code for the binaural-detection model used in the publication arXiv:2111.04637
This repository contains the code for the binaural-detection model used in the publication arXiv:2111.04637 Dependencies The model depends on the foll
Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems
Learning an Adaptive Meta Model-Generator for Incrementally Updating Recommender Systems This is our experimental code for RecSys 2021 paper "Learning
My implementation of Image Inpainting - A deep learning Inpainting model
Image Inpainting What is Image Inpainting Image inpainting is a restorative process that allows for the fixing or removal of unwanted parts within ima
TensorFlow 2 implementation of the Yahoo Open-NSFW model
TensorFlow 2 implementation of the Yahoo Open-NSFW model
Proof-Of-Concept Piano-Drums Music AI Model/Implementation
Rock Piano "When all is one and one is all, that's what it is to be a rock and not to roll." ---Led Zeppelin, "Stairway To Heaven" Proof-Of-Concept Pi
🦅 Pretrained BigBird Model for Korean (up to 4096 tokens)
Pretrained BigBird Model for Korean What is BigBird • How to Use • Pretraining • Evaluation Result • Docs • Citation 한국어 | English What is BigBird? Bi
PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, wav2lip, picture repair, image editing, photo2cartoon, image style transfer, and so on.
English | 简体中文 PaddleGAN PaddleGAN provides developers with high-performance implementation of classic and SOTA Generative Adversarial Networks, and s
Code for our paper "MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction" published at ICCV 2021.
MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction This repository contains the code for the p
The official PyTorch code implementation of "Human Trajectory Prediction via Counterfactual Analysis" in ICCV 2021.
Human Trajectory Prediction via Counterfactual Analysis (CausalHTP) The official PyTorch code implementation of "Human Trajectory Prediction via Count
Sketch Your Own GAN: Customizing a GAN model with hand-drawn sketches.
Sketch Your Own GAN Project | Paper | Youtube | Slides Our method takes in one or a few hand-drawn sketches and customizes an off-the-shelf GAN to mat
Repository of the paper Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models at ML4AD @ NeurIPS 2021.
Compressing Sensor Data for Remote Assistance of Autonomous Vehicles using Deep Generative Models Code and supplementary materials Repository of the p
A tool to visualise the results of AlphaFold2 and inspect the quality of structural predictions
AlphaFold Analyser This program produces high quality visualisations of predicted structures produced by AlphaFold. These visualisations allow the use
Autonomous Ground Vehicle Navigation and Control Simulation Examples in Python
Autonomous Ground Vehicle Navigation and Control Simulation Examples in Python THIS PROJECT IS CURRENTLY A WORK IN PROGRESS AND THUS THIS REPOSITORY I
'A C2C E-COMMERCE TRUST MODEL BASED ON REPUTATION' Python implementation
Project description A library providing functionalities to calculate reputation and degree of trust on C2C ecommerce platforms. The work is fully base
SOTA model in CIFAR10
A PyTorch Implementation of CIFAR Tricks 调研了CIFAR10数据集上各种trick,数据增强,正则化方法,并进行了实现。目前项目告一段落,如果有更好的想法,或者希望一起维护这个项目可以提issue或者在我的主页找到我的联系方式。 0. Requirement
In this Repo a simple Sklearn Model will be trained and pushed to MLFlow
SKlearn_to_MLFLow In this Repo a simple Sklearn Model will be trained and pushed to MLFlow Install This Repo is based on poetry python3 -m venv .venv
Auto HMM: Automatic Discrete and Continous HMM including Model selection
Auto HMM: Automatic Discrete and Continous HMM including Model selection
Replication of Pix2Seq with Pretrained Model
Pretrained-Pix2Seq We provide the pre-trained model of Pix2Seq. This version contains new data augmentation. The model is trained for 300 epochs and c
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment
Arch-Net: Model Distillation for Architecture Agnostic Model Deployment The official implementation of Arch-Net: Model Distillation for Architecture A
Data-Driven Operational Space Control for Adaptive and Robust Robot Manipulation
OSCAR Project Page | Paper This repository contains the codebase used in OSCAR: Data-Driven Operational Space Control for Adaptive and Robust Robot Ma
[ICML'21] Estimate the accuracy of the classifier in various environments through self-supervision
What Does Rotation Prediction Tell Us about Classifier Accuracy under Varying Testing Environments? [Paper] [ICML'21 Project] PyTorch Implementation T
Suite of tools for retrieving USGS NWIS observations and evaluating National Water Model (NWM) data.
Documentation OWPHydroTools GitHub pages documentation Motivation We developed OWPHydroTools with data scientists in mind. We attempted to ensure the
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
A Simple Framwork for CV Pre-training Model (SOCO, VirTex, BEiT)
A pytorch-based real-time segmentation model for autonomous driving
CFPNet: Channel-Wise Feature Pyramid for Real-Time Semantic Segmentation This project contains the Pytorch implementation for the proposed CFPNet: pap
Code for EMNLP2021 paper "Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training"
VoCapXLM Code for EMNLP2021 paper Allocating Large Vocabulary Capacity for Cross-lingual Language Model Pre-training Environment DockerFile: dancingso
An Open-Source Toolkit for Prompt-Learning.
An Open-Source Framework for Prompt-learning. Overview • Installation • How To Use • Docs • Paper • Citation • What's New? Nov 2021: Now we have relea
Causal-BALD: Deep Bayesian Active Learning of Outcomes to Infer Treatment-Effects from Observational Data.
causal-bald | Abstract | Installation | Example | Citation | Reproducing Results DUE An implementation of the methods presented in Causal-BALD: Deep B
Official implementation of "Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention" (BMVC 2021).
Multi-Glimpse Network Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention arXiv Require
This project aims to be a handler for input creation and running of multiple RICEWQ simulations.
What is autoRICEWQ? This project aims to be a handler for input creation and running of multiple RICEWQ simulations. What is RICEWQ? From the descript
A python library for highly configurable transformers - easing model architecture search and experimentation.
A python library for highly configurable transformers - easing model architecture search and experimentation.
An efficient and easy-to-use deep learning model compression framework
TinyNeuralNetwork 简体中文 TinyNeuralNetwork is an efficient and easy-to-use deep learning model compression framework, which contains features like neura
CBMPy Metadraft: a flexible and extensible genome-scale model reconstruction tool
CBMPy Metadraft: a flexible and extensible, GUI-based genome-scale model reconstruction tool that supports multiple Systems Biology standards.
An atmospheric growth and evolution model based on the EVo degassing model and FastChem 2.0
EVolve Linking planetary mantles to atmospheric chemistry through volcanism using EVo and FastChem. Overview EVolve is a linked mantle degassing and a
This repository contains the source code of an efficient 1D probabilistic model for music time analysis proposed in ICASSP2022 venue.
Jump Reward Inference for 1D Music Rhythmic State Spaces An implementation of the probablistic jump reward inference model for music rhythmic informat
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining
RMNA: A Neighbor Aggregation-Based Knowledge Graph Representation Learning Model Using Rule Mining Our code is based on Learning Attention-based Embed
Implicit Model Specialization through DAG-based Decentralized Federated Learning
Federated Learning DAG Experiments This repository contains software artifacts to reproduce the experiments presented in the Middleware '21 paper "Imp
The code for the NeurIPS 2021 paper "A Unified View of cGANs with and without Classifiers".
Energy-based Conditional Generative Adversarial Network (ECGAN) This is the code for the NeurIPS 2021 paper "A Unified View of cGANs with and without
Agent-based model simulator for air quality and pandemic risk assessment in architectural spaces
Agent-based model simulation for air quality and pandemic risk assessment in architectural spaces. User Guide archABM is a fast and open source agent-
A denoising diffusion probabilistic model synthesises galaxies that are qualitatively and physically indistinguishable from the real thing.
Realistic galaxy simulation via score-based generative models Official code for 'Realistic galaxy simulation via score-based generative models'. We us
Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together
SpeechMix Explore different way to mix speech model(wav2vec2, hubert) and nlp model(BART,T5,GPT) together. Introduction For the same input: from datas
This is the official Pytorch implementation of the paper "Diverse Motion Stylization for Multiple Style Domains via Spatial-Temporal Graph-Based Generative Model"
Diverse Motion Stylization (Official) This is the official Pytorch implementation of this paper. Diverse Motion Stylization for Multiple Style Domains
PyTorch implementation of a Real-ESRGAN model trained on custom dataset
Real-ESRGAN PyTorch implementation of a Real-ESRGAN model trained on custom dataset. This model shows better results on faces compared to the original
A toolkit for geo ML data processing and model evaluation (fork of solaris)
An open source ML toolkit for overhead imagery. This is a beta version of lunular which may continue to develop. Please report any bugs through issues
Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for prediction.
Predicitng_viability Using Streamlit to host a multi-page tool with model specs and classification metrics, while also accepting user input values for
Code for "Discovering Non-monotonic Autoregressive Orderings with Variational Inference" (paper and code updated from ICLR 2021)
Discovering Non-monotonic Autoregressive Orderings with Variational Inference Description This package contains the source code implementation of the
Python library for analysis of time series data including dimensionality reduction, clustering, and Markov model estimation
deeptime Releases: Installation via conda recommended. conda install -c conda-forge deeptime pip install deeptime Documentation: deeptime-ml.github.io
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis
A Shading-Guided Generative Implicit Model for Shape-Accurate 3D-Aware Image Synthesis Figure: Shape-Accurate 3D-Aware Image Synthesis. A Shading-Guid
A Factor Model for Persistence in Investment Manager Performance
Factor-Model-Manager-Performance A Factor Model for Persistence in Investment Manager Performance I apply methods and processes similar to those used
A complete end-to-end machine learning portal that covers processes starting from model training to the model predicting results using FastAPI.
Machine Learning Portal Goal Application Workflow Process Design Live Project Goal A complete end-to-end machine learning portal that covers processes
[NeurIPS 2021] "Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks" by Yonggan Fu, Qixuan Yu, Yang Zhang, Shang Wu, Xu Ouyang, David Cox, Yingyan Lin
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized Networks Yonggan Fu, Qixuan Yu, Yang Zhang, S
Structural Constraints on Information Content in Human Brain States
Structural Constraints on Information Content in Human Brain States Code accompanying the paper "The information content of brain states is explained
A transformer model to predict pathogenic mutations
MutFormer MutFormer is an application of the BERT (Bidirectional Encoder Representations from Transformers) NLP (Natural Language Processing) model wi
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021)
OREO: Object-Aware Regularization for Addressing Causal Confusion in Imitation Learning (NeurIPS 2021) Video demo We here provide a video demo from co
Easily Process a Batch of Cox Models
ezcox: Easily Process a Batch of Cox Models The goal of ezcox is to operate a batch of univariate or multivariate Cox models and return tidy result. ⏬
Invariant Causal Prediction for Block MDPs
MISA Abstract Generalization across environments is critical to the successful application of reinforcement learning algorithms to real-world challeng
Testing and Estimation of structural breaks in Stata
xtbreak estimating and testing for many known and unknown structural breaks in time series and panel data. For an overview of xtbreak test see xtbreak