1300 Repositories
Python probabilistic-graphical-models Libraries
Hierarchical Few-Shot Generative Models
Hierarchical Few-Shot Generative Models Giorgio Giannone, Ole Winther This repo contains code and experiments for the paper Hierarchical Few-Shot Gene
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching This is our attempt of the shared task on Quan
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
๐ค Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | ็ฎไฝไธญๆ | ็น้ซไธญๆ | ํ๊ตญ์ด State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow ๐ค Transformers provides thousands of pretrai
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
A PyTorch-based library for fast prototyping and sharing of deep neural network models.
pytorch implementation of the ICCV'21 paper "MVTN: Multi-View Transformation Network for 3D Shape Recognition"
MVTN: Multi-View Transformation Network for 3D Shape Recognition (ICCV 2021) By Abdullah Hamdi, Silvio Giancola, Bernard Ghanem Paper | Video | Tutori
PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data.
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. Check the unlearning effect
A little Python application to auto tag your photos with the power of machine learning.
Tag Machine A little Python application to auto tag your photos with the power of machine learning. Report a bug or request a feature Table of Content
Segmentation models with pretrained backbones. PyTorch.
Python library with Neural Networks for Image Segmentation based on PyTorch. The main features of this library are: High level API (just two lines to
This code provides various models combining dilated convolutions with residual networks
Overview This code provides various models combining dilated convolutions with residual networks. Our models can achieve better performance with less
PyTorch and Tensorflow functional model definitions
functional-zoo Model definitions and pretrained weights for PyTorch and Tensorflow PyTorch, unlike lua torch, has autograd in it's core, so using modu
PyTorch implementation of Octave Convolution with pre-trained Oct-ResNet and Oct-MobileNet models
octconv.pytorch PyTorch implementation of Octave Convolution in Drop an Octave: Reducing Spatial Redundancy in Convolutional Neural Networks with Octa
This repository is the official implementation of Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regularized Fine-Tuning (NeurIPS21).
Core-tuning This repository is the official implementation of ``Unleashing the Power of Contrastive Self-Supervised Visual Models via Contrast-Regular
This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Developed By Google!
Machine Learning Hand Detector This is a Machine Learning Based Hand Detector Project, It Uses Machine Learning Models and Modules Like Mediapipe, Dev
High-fidelity performance metrics for generative models in PyTorch
High-fidelity performance metrics for generative models in PyTorch
This is the code of NeurIPS'21 paper "Towards Enabling Meta-Learning from Target Models".
ST This is the code of NeurIPS 2021 paper "Towards Enabling Meta-Learning from Target Models". If you use any content of this repo for your work, plea
Collections of pydantic models
pydantic-collections The pydantic-collections package provides BaseCollectionModel class that allows you to manipulate collections of pydantic models
HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow
Class HiddenMarkovModel HiddenMarkovModel implements hidden Markov models with Gaussian mixtures as distributions on top of TensorFlow 2.0 Installatio
A collection of models for image-text generation in ACM MM 2021.
Bi-directional Image and Text Generation UMT-BITG (image & text generator) Unifying Multimodal Transformer for Bi-directional Image and Text Generatio
Joint Gaussian Graphical Model Estimation: A Survey
Joint Gaussian Graphical Model Estimation: A Survey Test Models Fused graphical lasso [1] Group graphical lasso [1] Graphical lasso [1] Doubly joint s
Extremely simple and fast extreme multi-class and multi-label classifiers.
napkinXC napkinXC is an extremely simple and fast library for extreme multi-class and multi-label classification, that focus of implementing various m
This repository contains all source code, pre-trained models related to the paper "An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator"
An Empirical Study on GANs with Margin Cosine Loss and Relativistic Discriminator This is a Pytorch implementation for the paper "An Empirical Study o
A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, color transfer, and gradient flow.
BoMb-OT Python3 implementation of the papers On Transportation of Mini-batches: A Hierarchical Approach and Improving Mini-batch Optimal Transport via
NeurIPS'21: Probabilistic Margins for Instance Reweighting in Adversarial Training (Pytorch implementation).
source code for NeurIPS21 paper robabilistic Margins for Instance Reweighting in Adversarial Training
Reverse engineer your pytorch vision models, in style
๐ Rover Reverse engineer your CNNs, in style Rover will help you break down your CNN and visualize the features from within the model. No need to wri
A bunch of random PyTorch models using PyTorch's C++ frontend
PyTorch Deep Learning Models using the C++ frontend Gettting started Clone the repo 1. https://github.com/mrdvince/pytorchcpp 2. cd fashionmnist or
A Word Level Transformer layer based on PyTorch and ๐ค Transformers.
Transformer Embedder A Word Level Transformer layer based on PyTorch and ๐ค Transformers. How to use Install the library from PyPI: pip install transf
LWCC: A LightWeight Crowd Counting library for Python that includes several pretrained state-of-the-art models.
LWCC: A LightWeight Crowd Counting library for Python LWCC is a lightweight crowd counting framework for Python. It wraps four state-of-the-art models
JittorVis - Visual understanding of deep learning models
JittorVis: Visual understanding of deep learning model JittorVis is an open-source library for understanding the inner workings of Jittor models by vi
A modular framework for vision & language multimodal research from Facebook AI Research (FAIR)
MMF is a modular framework for vision and language multimodal research from Facebook AI Research. MMF contains reference implementations of state-of-t
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.
[EMNLP 2021] Mirror-BERT: Converting Pretrained Language Models to universal text encoders without labels.
Train a state-of-the-art yolov3 object detector from scratch!
TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c
NLMpy - A Python package to create neutral landscape models
NLMpy is a Python package for the creation of neutral landscape models that are widely used by landscape ecologists to model ecological patterns
Learning to Prompt for Vision-Language Models.
CoOp Paper: Learning to Prompt for Vision-Language Models Authors: Kaiyang Zhou, Jingkang Yang, Chen Change Loy, Ziwei Liu CoOp (Context Optimization)
A collection of models for image - text generation in ACM MM 2021.
Bi-directional Image and Text Generation UMT-BITG (image & text generator) Unifying Multimodal Transformer for Bi-directional Image and Text Generatio
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
Finetuner allows one to tune the weights of any deep neural network for better embeddings on search tasks
PyTorch implementation of D2C: Diffuison-Decoding Models for Few-shot Conditional Generation.
D2C: Diffuison-Decoding Models for Few-shot Conditional Generation Project | Paper PyTorch implementation of D2C: Diffuison-Decoding Models for Few-sh
Rendering color and depth images for ShapeNet models.
Color & Depth Renderer for ShapeNet This library includes the tools for rendering multi-view color and depth images of ShapeNet models. Physically bas
PyTorch image models, scripts, pretrained weights -- ResNet, ResNeXT, EfficientNet, EfficientNetV2, NFNet, Vision Transformer, MixNet, MobileNet-V3/V2, RegNet, DPN, CSPNet, and more
PyTorch Image Models Sponsors What's New Introduction Models Features Results Getting Started (Documentation) Train, Validation, Inference Scripts Awe
First-Order Probabilistic Programming Language
FOPPL: A First-Order Probabilistic Programming Language This is an implementation of FOPPL, an S-expression based probabilistic programming language d
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)
Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee
Class activation maps for your PyTorch models (CAM, Grad-CAM, Grad-CAM++, Smooth Grad-CAM++, Score-CAM, SS-CAM, IS-CAM, XGrad-CAM, Layer-CAM)
TorchCAM: class activation explorer Simple way to leverage the class-specific activation of convolutional layers in PyTorch. Quick Tour Setting your C
An NLP library with Awesome pre-trained Transformer models and easy-to-use interface, supporting wide-range of NLP tasks from research to industrial applications.
็ฎไฝไธญๆ | English News [2021-10-12] PaddleNLP 2.1็ๆฌๅทฒๅๅธ๏ผๆฐๅขๅผ็ฎฑๅณ็จ็NLPไปปๅก่ฝๅใPrompt Tuningๅบ็จ็คบไพไธ็ๆไปปๅก็้ซๆง่ฝๆจ็๏ผ ๐ ๆดๅค่ฏฆ็ปๅ็บงไฟกๆฏ่ฏทๆฅ็Release Noteใ [2021-08-22]ใๅ่จ๏ผ้ขๅไบๅฎไธ่ดๆง็็
Production First and Production Ready End-to-End Speech Recognition Toolkit
WeNet ไธญๆ็ Discussions | Docs | Papers | Runtime (x86) | Runtime (android) | Pretrained Models We share neural Net together. The main motivation of WeN
High-quality implementations of standard and SOTA methods on a variety of tasks.
Uncertainty Baselines The goal of Uncertainty Baselines is to provide a template for researchers to build on. The baselines can be a starting point fo
Mengzi Pretrained Models
ไธญๆ | English Mengzi ๅฐฝ็ฎก้ข่ฎญ็ป่ฏญ่จๆจกๅๅจ NLP ็ๅไธช้ขๅ้ๅพๅฐไบๅนฟๆณ็ๅบ็จ๏ผไฝๆฏๅ ถ้ซๆ็ๆถ้ดๅ็ฎๅๆๆฌไพ็ถๆฏไธไธชไบ้่งฃๅณ็้ฎ้ขใ่ฟ่ฆๆฑๆไปฌๅจไธๅฎ็็ฎๅ็บฆๆไธ๏ผ็ ๅๅบๅ้กนๆๆ ๆดไผ็ๆจกๅใ ๆไปฌ็็ฎๆ ไธๆฏ่ฟฝๆฑๆดๅคง็ๆจกๅ่งๆจก๏ผ่ๆฏ่ฝป้็บงไฝๆดๅผบๅคง๏ผๅๆถๅฏน้จ็ฝฒๅๅทฅไธ่ฝๅฐๆดๅๅฅฝ็ๆจกๅใ
Scalable training for dense retrieval models.
Scalable implementation of dense retrieval. Training on cluster By default it trains locally: PYTHONPATH=.:$PYTHONPATH python dpr_scale/main.py traine
NVIDIA Merlin is an open source library providing end-to-end GPU-accelerated recommender systems, from feature engineering and preprocessing to training deep learning models and running inference in production.
NVIDIA Merlin NVIDIA Merlin is an open source library designed to accelerate recommender systems on NVIDIAโs GPUs. It enables data scientists, machine
A framework to train language models to learn invariant representations.
Invariant Language Modeling Implementation of the training for invariant language models. Motivation Modern pretrained language models are critical co
PixelPyramids: Exact Inference Models from Lossless Image Pyramids (ICCV 2021)
PixelPyramids: Exact Inference Models from Lossless Image Pyramids This repository contains the PyTorch implementation of the paper PixelPyramids: Exa
Discovering and Achieving Goals via World Models
Discovering and Achieving Goals via World Models [Project Website] [Benchmark Code] [Video (2min)] [Oral Talk (13min)] [Paper] Russell Mendonca*1, Ole
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch
A Library for Modelling Probabilistic Hierarchical Graphical Models in PyTorch
MIT-Machine Learning with PythonโFrom Linear Models to Deep Learning
MIT-Machine Learning with PythonโFrom Linear Models to Deep Learning | One of the 5 courses in MIT MicroMasters in Statistics & Data Science Welcome t
[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis
Focal Frequency Loss - Official PyTorch Implementation This repository provides the official PyTorch implementation for the following paper: Focal Fre
CadQuery is an intuitive, easy-to-use Python module for building parametric 3D CAD models.
A python parametric CAD scripting framework based on OCCT
Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.
Tensor2Tensor Tensor2Tensor, or T2T for short, is a library of deep learning models and datasets designed to make deep learning more accessible and ac
This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model inference.
PyTorch Infer Utils This package proposes simplified exporting pytorch models to ONNX and TensorRT, and also gives some base interface for model infer
Official pytorch implementation of Active Learning for deep object detection via probabilistic modeling (ICCV 2021)
Active Learning for Deep Object Detection via Probabilistic Modeling This repository is the official PyTorch implementation of Active Learning for Dee
Hapi is a Python library for building Conceptual Distributed Model using HBV96 lumped model & Muskingum routing method
Current build status All platforms: Current release info Name Downloads Version Platforms Hapi - Hydrological library for Python Hapi is an open-sourc
The Multi-Mission Maximum Likelihood framework (3ML)
PyPi Conda The Multi-Mission Maximum Likelihood framework (3ML) A framework for multi-wavelength/multi-messenger analysis for astronomy/astrophysics.
Tangram makes it easy for programmers to train, deploy, and monitor machine learning models.
Tangram Website | Discord Tangram makes it easy for programmers to train, deploy, and monitor machine learning models. Run tangram train to train a mo
A practical and feature-rich paraphrasing framework to augment human intents in text form to build robust NLU models for conversational engines. Created by Prithiviraj Damodaran. Open to pull requests and other forms of collaboration.
Parrot Parrot is a paraphrase based utterance augmentation framework purpose built to accelerate training NLU models. A paraphrase framework is more t
MaD GUI is a basis for graphical annotation and computational analysis of time series data.
MaD GUI Machine Learning and Data Analytics Graphical User Interface MaD GUI is a basis for graphical annotation and computational analysis of time se
PyPI package for scaffolding out code for decision tree models that can learn to find relationships between the attributes of an object.
Decision Tree Writer This package allows you to train a binary classification decision tree on a list of labeled dictionaries or class instances, and
Download videos and audio with a graphical interface in python
Youtube-Downloader Download videos and audio with a graphical interface in python Windows To run windows using Command Prompt python main.py linux To
Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE)
OG-SPACE Introduction Optimized Gillespie algorithm for simulating Stochastic sPAtial models of Cancer Evolution (OG-SPACE) is a computational framewo
Analysis of rationale selection in neural rationale models
Neural Rationale Interpretability Analysis We analyze the neural rationale models proposed by Lei et al. (2016) and Bastings et al. (2019), as impleme
Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees"
Companion code for "Bayesian logistic regression for online recalibration and revision of risk prediction models with performance guarantees" Installa
Benchmarking the robustness of Spatial-Temporal Models
Benchmarking the robustness of Spatial-Temporal Models This repositery contains the code for the paper Benchmarking the Robustness of Spatial-Temporal
Codebase of deep learning models for inferring stability of mRNA molecules
Kaggle OpenVaccine Models Codebase of deep learning models for inferring stability of mRNA molecules, corresponding to the Kaggle Open Vaccine Challen
The self-supervised goal reaching benchmark introduced in Discovering and Achieving Goals via World Models
Lexa-Benchmark Codebase for the self-supervised goal reaching benchmark introduced in 'Discovering and Achieving Goals via World Models'. Setup Create
Code & Data for the Paper "Time Masking for Temporal Language Models", WSDM 2022
Time Masking for Temporal Language Models This repository provides a reference implementation of the paper: Time Masking for Temporal Language Models
Neural text generators like the GPT models promise a general-purpose means of manipulating texts.
Boolean Prompting for Neural Text Generators Neural text generators like the GPT models promise a general-purpose means of manipulating texts. These m
Bayesian regularization for functional graphical models.
BayesFGM Paper: Jiajing Niu, Andrew Brown. Bayesian regularization for functional graphical models. Requirements R version 3.6.3 and up Python 3.6 and
New approach to benchmark VQA models
VQA Benchmarking This repository contains the web application & the python interface to evaluate VQA models. Documentation Please see the documentatio
Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems.
CottonWeeds Deep learning models for classification of 15 common weeds in the southern U.S. cotton production systems. requirements pytorch torchsumma
Repository sharing code and the model for the paper "Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes"
Rescoring Sequence-to-Sequence Models for Text Line Recognition with CTC-Prefixes Setup virtualenv -p python3 venv source venv/bin/activate pip instal
HyperCube: Implicit Field Representations of Voxelized 3D Models
HyperCube: Implicit Field Representations of Voxelized 3D Models Authors: Magdalena Proszewska, Marcin Mazur, Tomasz Trzcinski, Przemysลaw Spurek [Pap
This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.
This is the repository for paper NEEDLE: Towards Non-invertible Backdoor Attack to Deep Learning Models.
Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.
Toolkit for Building Robust ML models that generalize to unseen domains (RobustDG) Divyat Mahajan, Shruti Tople, Amit Sharma Privacy & Causal Learning
Pre-training BERT masked language models with custom vocabulary
Pre-training BERT Masked Language Models (MLM) This repository contains the method to pre-train a BERT model using custom vocabulary. It was used to p
Implementations of Machine Learning models, Regularizers, Optimizers and different Cost functions.
Linear Models Implementations of LinearRegression, LassoRegression and RidgeRegression with appropriate Regularizers and Optimizers. Linear Regression
cqMore is a CadQuery plugin based on CadQuery 2.1.
cqMore (under construction) cqMore is a CadQuery plugin based on CadQuery 2.1. Installation Please use conda to install CadQuery and its dependencies
A simple graphical interface for encrypting sentences
A simple graphical interface for encrypting sentences
A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.
A framework for evaluating Knowledge Graph Embedding Models in a fine-grained manner.
Text2Art is an AI art generator powered with VQGAN + CLIP and CLIPDrawer models
Text2Art is an AI art generator powered with VQGAN + CLIP and CLIPDrawer models. You can easily generate all kind of art from drawing, painting, sketch, or even a specific artist style just using a text input. You can also specify the dimensions of the image. The process can take 3-20 mins and the results will be emailed to you.
DeepCAD: A Deep Generative Network for Computer-Aided Design Models
DeepCAD This repository provides source code for our paper: DeepCAD: A Deep Generative Network for Computer-Aided Design Models Rundi Wu, Chang Xiao,
Training vision models with full-batch gradient descent and regularization
Stochastic Training is Not Necessary for Generalization -- Training competitive vision models without stochasticity This repository implements trainin
Blender addon to generate better building models from satellite imagery.
Blender addon to generate better building models from satellite imagery.
Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"
RNN-for-Joint-NLU Pytorch implementation of "Attention-Based Recurrent Neural Network Models for Joint Intent Detection and Slot Filling"
TorchXRayVision: A library of chest X-ray datasets and models.
torchxrayvision A library for chest X-ray datasets and models. Including pre-trained models. ( ๐ฌ promo video about the project) Motivation: While the
A pytorch-based deep learning framework for multi-modal 2D/3D medical image segmentation
A 3D multi-modal medical image segmentation library in PyTorch We strongly believe in open and reproducible deep learning research. Our goal is to imp
Explainer for black box models that predict molecule properties
Explaining why that molecule exmol is a package to explain black-box predictions of molecules. The package uses model agnostic explanations to help us
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks
Prompt-learning is the latest paradigm to adapt pre-trained language models (PLMs) to downstream NLP tasks, which modifies the input text with a textual template and directly uses PLMs to conduct pre-trained tasks. This library provides a standard, flexible and extensible framework to deploy the prompt-learning pipeline. OpenPrompt supports loading PLMs directly from huggingface transformers. In the future, we will also support PLMs implemented by other libraries.
pcnaDeep integrates cutting-edge detection techniques with tracking and cell cycle resolving models.
pcnaDeep: a deep-learning based single-cell cycle profiler with PCNA signal Welcome! pcnaDeep integrates cutting-edge detection techniques with tracki
A Chinese to English Neural Model Translation Project
ZH-EN NMT Chinese to English Neural Machine Translation This project is inspired by Stanford's CS224N NMT Project Dataset used in this project: News C
Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)
Pytorch implementation of paper "Efficient Nearest Neighbor Language Models" (EMNLP 2021)
A Python library for Deep Probabilistic Modeling
Abstract DeeProb-kit is a Python library that implements deep probabilistic models such as various kinds of Sum-Product Networks, Normalizing Flows an