1287 Repositories
Python Diffusion-Probabilistic-Models Libraries
A TensorFlow implementation of the Mnemonic Descent Method.
MDM A Tensorflow implementation of the Mnemonic Descent Method. Mnemonic Descent Method: A recurrent process applied for end-to-end face alignment G.
Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are implemented and can be seen in tensorboard.
Sarus published models Sarus implementation of classical ML models. The models are implemented using the Keras API of tensorflow 2. Vizualization are
Caffe models in TensorFlow
Caffe to TensorFlow Convert Caffe models to TensorFlow. Usage Run convert.py to convert an existing Caffe model to TensorFlow. Make sure you're using
Run Keras models in the browser, with GPU support using WebGL
**This project is no longer active. Please check out TensorFlow.js.** The Keras.js demos still work but is no longer updated. Run Keras models in the
Tensorflow/Keras Plug-N-Play Deep Learning Models Compilation
DeepBay This project was created with the objective of compile Machine Learning Architectures created using Tensorflow or Keras. The architectures mus
A design of MIDI language for music generation task, specifically for Natural Language Processing (NLP) models.
MIDI Language Introduction Reference Paper: Pop Music Transformer: Beat-based Modeling and Generation of Expressive Pop Piano Compositions: code This
SLAMP: Stochastic Latent Appearance and Motion Prediction
SLAMP: Stochastic Latent Appearance and Motion Prediction Official implementation of the paper SLAMP: Stochastic Latent Appearance and Motion Predicti
Face Detection with DLIB
Face Detection with DLIB In this project, we have detected our face with dlib and opencv libraries. Setup This Project Install DLIB & OpenCV You can i
The Codebase for Causal Distillation for Language Models.
Causal Distillation for Language Models Zhengxuan Wu*,Atticus Geiger*, Josh Rozner, Elisa Kreiss, Hanson Lu, Thomas Icard, Christopher Potts, Noah D.
PyTorch implementation of probabilistic deep forecast applied to air quality.
Probabilistic Deep Forecast PyTorch implementation of a paper, titled: Probabilistic Deep Learning to Quantify Uncertainty in Air Quality Forecasting
Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion Models
Label-Efficient Semantic Segmentation with Diffusion Models Official implementation of the paper Label-Efficient Semantic Segmentation with Diffusion
Train and use generative text models in a few lines of code.
blather Train and use generative text models in a few lines of code. To see blather in action check out the colab notebook! Installation Use the packa
An OpenAI-Gym Package for Training and Testing Reinforcement Learning algorithms with OpenSim Models
Authors: Utkarsh A. Mishra and Dr. Dimitar Stanev Advisors: Dr. Dimitar Stanev and Prof. Auke Ijspeert, Biorobotics Laboratory (BioRob), EPFL Video Pl
Convert ONNX model graph to Keras model format.
Convert ONNX model graph to Keras model format.
FedTorch is an open-source Python package for distributed and federated training of machine learning models using PyTorch distributed API
FedTorch is a generic repository for benchmarking different federated and distributed learning algorithms using PyTorch Distributed API.
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
AI Fairness 360 (AIF360) The AI Fairness 360 toolkit is an extensible open-source library containg techniques developed by the research community to h
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images
MetaAvatar: Learning Animatable Clothed Human Models from Few Depth Images This repository contains the implementation of our paper MetaAvatar: Learni
Official Pytorch implementation for 2021 ICCV paper "Learning Motion Priors for 4D Human Body Capture in 3D Scenes" and trained models / data
Learning Motion Priors for 4D Human Body Capture in 3D Scenes (LEMO) Official Pytorch implementation for 2021 ICCV (oral) paper "Learning Motion Prior
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
Code for the Paper "Diffusion Models for Handwriting Generation"
Code for the Paper "Diffusion Models for Handwriting Generation"
Implementation of Google Brain's WaveGrad high-fidelity vocoder
WaveGrad Implementation (PyTorch) of Google Brain's high-fidelity WaveGrad vocoder (paper). First implementation on GitHub with high-quality generatio
DiffWave is a fast, high-quality neural vocoder and waveform synthesizer.
DiffWave DiffWave is a fast, high-quality neural vocoder and waveform synthesizer. It starts with Gaussian noise and converts it into speech via itera
Symbolic Music Generation with Diffusion Models
Symbolic Music Generation with Diffusion Models Supplementary code release for our work Symbolic Music Generation with Diffusion Models. Installation
Implementation of "Adversarial purification with Score-based generative models", ICML 2021
Adversarial Purification with Score-based Generative Models by Jongmin Yoon, Sung Ju Hwang, Juho Lee This repository includes the official PyTorch imp
Reference implementation for Deep Unsupervised Learning using Nonequilibrium Thermodynamics
Diffusion Probabilistic Models This repository provides a reference implementation of the method described in the paper: Deep Unsupervised Learning us
Noise Conditional Score Networks (NeurIPS 2019, Oral)
Generative Modeling by Estimating Gradients of the Data Distribution This repo contains the official implementation for the NeurIPS 2019 paper Generat
The official PyTorch implementation for NCSNv2 (NeurIPS 2020)
Improved Techniques for Training Score-Based Generative Models This repo contains the official implementation for the paper Improved Techniques for Tr
PyTorch reimplementation of Diffusion Models
PyTorch pretrained Diffusion Models A PyTorch reimplementation of Denoising Diffusion Probabilistic Models with checkpoints converted from the author'
Denoising Diffusion Probabilistic Models
Denoising Diffusion Probabilistic Models Jonathan Ho, Ajay Jain, Pieter Abbeel Paper: https://arxiv.org/abs/2006.11239 Website: https://hojonathanho.g
Denoising Diffusion Implicit Models
Denoising Diffusion Implicit Models (DDIM) Jiaming Song, Chenlin Meng and Stefano Ermon, Stanford Implements sampling from an implicit model that is t
Diffusion Probabilistic Models for 3D Point Cloud Generation (CVPR 2021)
Diffusion Probabilistic Models for 3D Point Cloud Generation [Paper] [Code] The official code repository for our CVPR 2021 paper "Diffusion Probabilis
Jax/Flax implementation of Variational-DiffWave.
jax-variational-diffwave Jax/Flax implementation of Variational-DiffWave. (Zhifeng Kong et al., 2020, Diederik P. Kingma et al., 2021.) DiffWave with
PyTorch toolkit for biomedical imaging
farabio is a minimal PyTorch toolkit for out-of-the-box deep learning support in biomedical imaging. For further information, see Wikis and Docs.
A collection of resources and papers on Diffusion Models, a darkhorse in the field of Generative Models
This repository contains a collection of resources and papers on Diffusion Models and Score-based Models. If there are any missing valuable resources
Quick program made to generate alpha and delta tables for Hidden Markov Models
HMM_Calc Functions for generating Alpha and Delta tables from a Hidden Markov Model. Parameters: a: Matrix of transition probabilities. a[i][j] = a_{i
Pipeline for training LSA models using Scikit-Learn.
Latent Semantic Analysis Pipeline for training LSA models using Scikit-Learn. Usage Instead of writing custom code for latent semantic analysis, you j
GPT-3: Language Models are Few-Shot Learners
GPT-3: Language Models are Few-Shot Learners arXiv link Recent work has demonstrated substantial gains on many NLP tasks and benchmarks by pre-trainin
Official implementations for various pre-training models of ERNIE-family, covering topics of Language Understanding & Generation, Multimodal Understanding & Generation, and beyond.
English|简体中文 ERNIE是百度开创性提出的基于知识增强的持续学习语义理解框架,该框架将大数据预训练与多源丰富知识相结合,通过持续学习技术,不断吸收海量文本数据中词汇、结构、语义等方面的知识,实现模型效果不断进化。ERNIE在累积 40 余个典型 NLP 任务取得 SOTA 效果,并在 G
Revisiting Pre-trained Models for Chinese Natural Language Processing (Findings of EMNLP 2020)
This repository contains the resources in our paper "Revisiting Pre-trained Models for Chinese Natural Language Processing", which will be published i
Optimus: the first large-scale pre-trained VAE language model
Optimus: the first pre-trained Big VAE language model This repository contains source code necessary to reproduce the results presented in the EMNLP 2
(ACL-IJCNLP 2021) Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models.
BERT Convolutions Code for the paper Convolutions and Self-Attention: Re-interpreting Relative Positions in Pre-trained Language Models. Contains expe
Code for the ACL 2021 paper "Structural Guidance for Transformer Language Models"
Structural Guidance for Transformer Language Models This repository accompanies the paper, Structural Guidance for Transformer Language Models, publis
Research code for the paper "How Good is Your Tokenizer? On the Monolingual Performance of Multilingual Language Models"
Introduction This repository contains research code for the ACL 2021 paper "How Good is Your Tokenizer? On the Monolingual Performance of Multilingual
[CVPR 2021] VirTex: Learning Visual Representations from Textual Annotations
VirTex: Learning Visual Representations from Textual Annotations Karan Desai and Justin Johnson University of Michigan CVPR 2021 arxiv.org/abs/2006.06
Dense Passage Retriever - is a set of tools and models for open domain Q&A task.
Dense Passage Retrieval Dense Passage Retrieval (DPR) - is a set of tools and models for state-of-the-art open-domain Q&A research. It is based on the
Simple Python library, distributed via binary wheels with few direct dependencies, for easily using wav2vec 2.0 models for speech recognition
Wav2Vec2 STT Python Beta Software Simple Python library, distributed via binary wheels with few direct dependencies, for easily using wav2vec 2.0 mode
Toolkit for developing and maintaining ML models
modelkit Python framework for production ML systems. modelkit is a minimalist yet powerful MLOps library for Python, built for people who want to depl
PyTorch implementation for "HyperSPNs: Compact and Expressive Probabilistic Circuits", NeurIPS 2021
HyperSPN This repository contains code for the paper: HyperSPNs: Compact and Expressive Probabilistic Circuits "HyperSPNs: Compact and Expressive Prob
AAAI 2022: Stationary diffusion state neural estimation
Stationary Diffusion State Neural Estimation Although many graph-based clustering methods attempt to model the stationary diffusion state in their obj
CoRe: Contrastive Recurrent State-Space Models
CoRe: Contrastive Recurrent State-Space Models This code implements the CoRe model and reproduces experimental results found in Robust Robotic Control
Milano is a tool for automating hyper-parameters search for your models on a backend of your choice.
Milano (This is a research project, not an official NVIDIA product.) Documentation https://nvidia.github.io/Milano Milano (Machine learning autotuner
Code & Models for Temporal Segment Networks (TSN) in ECCV 2016
Temporal Segment Networks (TSN) We have released MMAction, a full-fledged action understanding toolbox based on PyTorch. It includes implementation fo
DenseNet Implementation in Keras with ImageNet Pretrained Models
DenseNet-Keras with ImageNet Pretrained Models This is an Keras implementation of DenseNet with ImageNet pretrained weights. The weights are converted
Code and pre-trained models for "ReasonBert: Pre-trained to Reason with Distant Supervision", EMNLP'2021
ReasonBERT Code and pre-trained models for ReasonBert: Pre-trained to Reason with Distant Supervision, EMNLP'2021 Pretrained Models The pretrained mod
Implementation of the paper 'Sentence Bottleneck Autoencoders from Transformer Language Models'
Introduction This repository contains the code for the paper Sentence Bottleneck Autoencoders from Transformer Language Models by Ivan Montero, Nikola
Diagnostic tests for linguistic capacities in language models
LM diagnostics This repository contains the diagnostic datasets and experimental code for What BERT is not: Lessons from a new suite of psycholinguist
Code for Editing Factual Knowledge in Language Models
KnowledgeEditor Code for Editing Factual Knowledge in Language Models (https://arxiv.org/abs/2104.08164). @inproceedings{decao2021editing, title={Ed
Code for ACL2021 long paper: Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases
LANKA This is the source code for paper: Knowledgeable or Educated Guess? Revisiting Language Models as Knowledge Bases (ACL 2021, long paper) Referen
The official implementation of "BERT is to NLP what AlexNet is to CV: Can Pre-Trained Language Models Identify Analogies?, ACL 2021 main conference"
BERT is to NLP what AlexNet is to CV This is the official implementation of BERT is to NLP what AlexNet is to CV: Can Pre-Trained Language Models Iden
Super Tickets in Pre-Trained Language Models: From Model Compression to Improving Generalization (ACL 2021)
Structured Super Lottery Tickets in BERT This repo contains our codes for the paper "Super Tickets in Pre-Trained Language Models: From Model Compress
ACL'2021: LM-BFF: Better Few-shot Fine-tuning of Language Models
LM-BFF (Better Few-shot Fine-tuning of Language Models) This is the implementation of the paper Making Pre-trained Language Models Better Few-shot Lea
PyTorch source code of NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models"
This repository contains source code for NAACL 2019 paper "An Embarrassingly Simple Approach for Transfer Learning from Pretrained Language Models" (P
Source code for the ACL-IJCNLP 2021 paper entitled "T-DNA: Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adaptation" by Shizhe Diao et al.
T-DNA Source code for the ACL-IJCNLP 2021 paper entitled Taming Pre-trained Language Models with N-gram Representations for Low-Resource Domain Adapta
The code is the training example of AAAI2022 Security AI Challenger Program Phase 8: Data Centric Robot Learning on ML models.
Example code of [Tianchi AAAI2022 Security AI Challenger Program Phase 8]
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"
This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur
Semi-automated vocabulary generation from semantic vector models
vec2word Semi-automated vocabulary generation from semantic vector models This script generates a list of potential conlang word forms along with asso
Dataset for the Research2Clinics @ NeurIPS 2021 Paper: What Do You See in this Patient? Behavioral Testing of Clinical NLP Models
Behavioral Testing of Clinical NLP Models This repository contains code for testing the behavior of clinical prediction models based on patient letter
Codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense neural networks
DominoSearch This is repository for codes and models of NeurIPS2021 paper - DominoSearch: Find layer-wise fine-grained N:M sparse schemes from dense n
Official implementation of Representer Point Selection via Local Jacobian Expansion for Post-hoc Classifier Explanation of Deep Neural Networks and Ensemble Models at NeurIPS 2021
Representer Point Selection via Local Jacobian Expansion for Classifier Explanation of Deep Neural Networks and Ensemble Models This repository is the
Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting
QAConv Interpretable and Generalizable Person Re-Identification with Query-Adaptive Convolution and Temporal Lifting This PyTorch code is proposed in
This repository is for the preprint "A generative nonparametric Bayesian model for whole genomes"
BEAR Overview This repository contains code associated with the preprint A generative nonparametric Bayesian model for whole genomes (2021), which pro
Probabilistic Tensor Decomposition of Neural Population Spiking Activity
Probabilistic Tensor Decomposition of Neural Population Spiking Activity Matlab (recommended) and Python (in developement) implementations of Soulat e
'Aligned mixture of latent dynamical systems' (amLDS) for stimulus decoding probabilistic manifold alignment across animals. P. Herrero-Vidal et al. NeurIPS 2021 code.
Across-animal odor decoding by probabilistic manifold alignment (NeurIPS 2021) This repository is the official implementation of aligned mixture of la
Code for "On Memorization in Probabilistic Deep Generative Models"
On Memorization in Probabilistic Deep Generative Models This repository contains the code necessary to reproduce the experiments in On Memorization in
Deep Latent Force Models
Deep Latent Force Models This repository contains a PyTorch implementation of the deep latent force model (DLFM), presented in the paper, Compositiona
[NeurIPS 2021] Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples | ⛰️⚠️
Towards Better Understanding of Training Certifiably Robust Models against Adversarial Examples This repository is the official implementation of "Tow
Auditing Black-Box Prediction Models for Data Minimization Compliance
Data-Minimization-Auditor An auditing tool for model-instability based data minimization that is introduced in "Auditing Black-Box Prediction Models f
Think Big, Teach Small: Do Language Models Distil Occam’s Razor?
Think Big, Teach Small: Do Language Models Distil Occam’s Razor? Software related to the paper "Think Big, Teach Small: Do Language Models Distil Occa
Code for models used in Bashiri et al., "A Flow-based latent state generative model of neural population responses to natural images".
A Flow-based latent state generative model of neural population responses to natural images Code for "A Flow-based latent state generative model of ne
Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models
LMPBT Supplementary code for the Paper entitled ``Locally Most Powerful Bayesian Test for Out-of-Distribution Detection using Deep Generative Models"
Evolutionary Scale Modeling (esm): Pretrained language models for proteins
Evolutionary Scale Modeling This repository contains code and pre-trained weights for Transformer protein language models from Facebook AI Research, i
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models
PipeTransformer: Automated Elastic Pipelining for Distributed Training of Large-scale Models This repository is the official implementation of the fol
A paper list of pre-trained language models (PLMs).
Large-scale pre-trained language models (PLMs) such as BERT and GPT have achieved great success and become a milestone in NLP.
PySlowFast: video understanding codebase from FAIR for reproducing state-of-the-art video models.
PySlowFast PySlowFast is an open source video understanding codebase from FAIR that provides state-of-the-art video classification models with efficie
Behavioral Testing of Clinical NLP Models
Behavioral Testing of Clinical NLP Models This repository contains code for testing the behavior of clinical prediction models based on patient letter
Numba-accelerated Pythonic implementation of MPDATA with examples in Python, Julia and Matlab
PyMPDATA PyMPDATA is a high-performance Numba-accelerated Pythonic implementation of the MPDATA algorithm of Smolarkiewicz et al. used in geophysical
OpenL3: Open-source deep audio and image embeddings
OpenL3 OpenL3 is an open-source Python library for computing deep audio and image embeddings. Please refer to the documentation for detailed instructi
Datasets, Transforms and Models specific to Computer Vision
vision Datasets, Transforms and Models specific to Computer Vision Installation First install the nightly version of OneFlow python3 -m pip install on
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
Set of methods to ensemble boxes from different object detection models, including implementation of "Weighted boxes fusion (WBF)" method.
Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis
Official implementation of VQ-Diffusion: Vector Quantized Diffusion Model for Text-to-Image Synthesis
Code for paper "Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs"
This is the codebase for the paper: Do Language Models Have Beliefs? Methods for Detecting, Updating, and Visualizing Model Beliefs Directory Structur
The first GANs-based omics-to-omics translation framework
OmiTrans Please also have a look at our multi-omics multi-task DL freamwork 👀 : OmiEmbed The FIRST GANs-based omics-to-omics translation framework Xi
A benchmark dataset for emulating atmospheric radiative transfer in weather and climate models with machine learning (NeurIPS 2021 Datasets and Benchmarks Track)
ClimART - A Benchmark Dataset for Emulating Atmospheric Radiative Transfer in Weather and Climate Models Official PyTorch Implementation Using deep le
Official implementation of VQ-Diffusion
Vector Quantized Diffusion Model for Text-to-Image Synthesis Overview This is the official repo for the paper: [Vector Quantized Diffusion Model for T
Official implementation for: Blended Diffusion for Text-driven Editing of Natural Images.
Blended Diffusion for Text-driven Editing of Natural Images Blended Diffusion for Text-driven Editing of Natural Images Omri Avrahami, Dani Lischinski
Molecular Sets (MOSES): A Benchmarking Platform for Molecular Generation Models
Molecular Sets (MOSES): A benchmarking platform for molecular generation models Deep generative models are rapidly becoming popular for the discovery
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Models
GraphRNN: Generating Realistic Graphs with Deep Auto-regressive Model This repository is the official PyTorch implementation of GraphRNN, a graph gene
Pre-trained Deep Learning models and demos (high quality and extremely fast)
OpenVINO™ Toolkit - Open Model Zoo repository This repository includes optimized deep learning models and a set of demos to expedite development of hi
An open-source Kazakh named entity recognition dataset (KazNERD), annotation guidelines, and baseline NER models.
Kazakh Named Entity Recognition This repository contains an open-source Kazakh named entity recognition dataset (KazNERD), named entity annotation gui
Simple command line tool to train and deploy your machine learning models with AWS SageMaker
metamaker Simple command line tool to train and deploy your machine learning models with AWS SageMaker Features metamaker enables you to: Build a dock