3550 Repositories
Python deep-models Libraries
Fast SHAP value computation for interpreting tree-based models
FastTreeSHAP FastTreeSHAP package is built based on the paper Fast TreeSHAP: Accelerating SHAP Value Computation for Trees published in NeurIPS 2021 X
codebase for "A Theory of the Inductive Bias and Generalization of Kernel Regression and Wide Neural Networks"
Eigenlearning This repo contains code for replicating the experiments of the paper A Theory of the Inductive Bias and Generalization of Kernel Regress
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology (LMRL Workshop, NeurIPS 2021)
Self-Supervised Vision Transformers Learn Visual Concepts in Histopathology Self-Supervised Vision Transformers Learn Visual Concepts in Histopatholog
Contextual Attention Network: Transformer Meets U-Net
Contextual Attention Network: Transformer Meets U-Net Contexual attention network for medical image segmentation with state of the art results on skin
Package towards building Explainable Forecasting and Nowcasting Models with State-of-the-art Deep Neural Networks and Dynamic Factor Model on Time Series data sets with single line of code. Also, provides utilify facility for time-series signal similarities matching, and removing noise from timeseries signals.
DeepXF: Explainable Forecasting and Nowcasting with State-of-the-art Deep Neural Networks and Dynamic Factor Model Also, verify TS signal similarities
🚀 RocketQA, dense retrieval for information retrieval and question answering, including both Chinese and English state-of-the-art models.
In recent years, the dense retrievers based on pre-trained language models have achieved remarkable progress. To facilitate more developers using cutt
SciFive: a text-text transformer model for biomedical literature
SciFive SciFive provided a Text-Text framework for biomedical language and natural language in NLP. Under the T5's framework and desrbibed in the pape
GARCH and Multivariate LSTM forecasting models for Bitcoin realized volatility with potential applications in crypto options trading, hedging, portfolio management, and risk management
Bitcoin Realized Volatility Forecasting with GARCH and Multivariate LSTM Author: Chi Bui This Repository Repository Directory ├── README.md
TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
TorchMultimodal (Alpha Release) Introduction TorchMultimodal is a PyTorch library for training state-of-the-art multimodal multi-task models at scale.
[CVPR 2022] Pytorch implementation of "Templates for 3D Object Pose Estimation Revisited: Generalization to New objects and Robustness to Occlusions" paper
template-pose Pytorch implementation of "Templates for 3D Object Pose Estimation Revisited: Generalization to New objects and Robustness to Occlusions
Official PyTorch implementation of the paper "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.
Deep Constrained Least Squares for Blind Image Super-Resolution [Paper] This is the official implementation of 'Deep Constrained Least Squares for Bli
UT-Sarulab MOS prediction system using SSL models
UTMOS: UTokyo-SaruLab MOS Prediction System Official implementation of "UTMOS: UTokyo-SaruLab System for VoiceMOS Challenge 2022" submitted to INTERSP
(CVPR 2022 - oral) Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry
Multi-View Depth Estimation by Fusing Single-View Depth Probability with Multi-View Geometry Official implementation of the paper Multi-View Depth Est
Official code for "Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes", CVPR2022
[CVPR 2022] Eigenlanes: Data-Driven Lane Descriptors for Structurally Diverse Lanes Dongkwon Jin, Wonhui Park, Seong-Gyun Jeong, Heeyeon Kwon, and Cha
The PyTorch implementation for paper "Neural Texture Extraction and Distribution for Controllable Person Image Synthesis" (CVPR2022 Oral)
ArXiv | Get Start Neural-Texture-Extraction-Distribution The PyTorch implementation for our paper "Neural Texture Extraction and Distribution for Cont
Everything you want about DP-Based Federated Learning, including Papers and Code. (Mechanism: Laplace or Gaussian, Dataset: femnist, shakespeare, mnist, cifar-10 and fashion-mnist. )
Differential Privacy (DP) Based Federated Learning (FL) Everything about DP-based FL you need is here. (所有你需要的DP-based FL的信息都在这里) Code Tip: the code o
Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in Pytorch
Retrieval-Augmented Denoising Diffusion Probabilistic Models (wip) Implementation of Retrieval-Augmented Denoising Diffusion Probabilistic Models in P
[ICLR 2022] Pretraining Text Encoders with Adversarial Mixture of Training Signal Generators
AMOS This repository contains the scripts for fine-tuning AMOS pretrained models on GLUE and SQuAD 2.0 benchmarks. Paper: Pretraining Text Encoders wi
ACL22 paper: Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost
Imputing Out-of-Vocabulary Embeddings with LOVE Makes Language Models Robust with Little Cost LOVE is accpeted by ACL22 main conference as a long pape
Pytoydl: A toy deep learning framework built upon numpy.
Documents: https://pytoydl.readthedocs.io/zh/latest/ Pytoydl A toy deep learning framework built upon numpy. You can star this repository to keep trac
[CVPR'22] Official PyTorch Implementation of Collaborative Transformers for Grounded Situation Recognition
[CVPR'22] Collaborative Transformers for Grounded Situation Recognition Paper | Model Checkpoint This is the official PyTorch implementation of Collab
Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capability)
Protein GLM (wip) Implementation of a protein autoregressive language model, but with autoregressive infilling objective (editing subsequences capabil
A port of muP to JAX/Haiku
MUP for Haiku This is a (very preliminary) port of Yang and Hu et al.'s μP repo to Haiku and JAX. It's not feature complete, and I'm very open to sugg
Pretrained models for Jax/Haiku; MobileNet, ResNet, VGG, Xception.
Pre-trained image classification models for Jax/Haiku Jax/Haiku Applications are deep learning models that are made available alongside pre-trained we
Contains code for Deep Kernelized Dense Geometric Matching
DKM - Deep Kernelized Dense Geometric Matching Contains code for Deep Kernelized Dense Geometric Matching We provide pretrained models and code for ev
Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel order of RGB and BGR. Simple Channel Converter for ONNX.
scc4onnx Very simple NCHW and NHWC conversion tool for ONNX. Change to the specified input order for each and every input OP. Also, change the channel
SIGIR'22 paper: Axiomatically Regularized Pre-training for Ad hoc Search
Introduction This codebase contains source-code of the Python-based implementation (ARES) of our SIGIR 2022 paper. Chen, Jia, et al. "Axiomatically Re
Repository for fine-tuning Transformers 🤗 based seq2seq speech models in JAX/Flax.
Seq2Seq Speech in JAX A JAX/Flax repository for combining a pre-trained speech encoder model (e.g. Wav2Vec2, HuBERT, WavLM) with a pre-trained text de
Implementation of 🦩 Flamingo, state-of-the-art few-shot visual question answering attention net out of Deepmind, in Pytorch
🦩 Flamingo - Pytorch Implementation of Flamingo, state-of-the-art few-shot visual question answering attention net, in Pytorch. It will include the p
Direct application of DALLE-2 to video synthesis, using factored space-time Unet and Transformers
DALLE2 Video (wip) ** only to be built after DALLE2 image is done and replicated, and the importance of the prior network is validated ** Direct appli
Code for "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" paper
UNICORN 🦄 Webpage | Paper | BibTex PyTorch implementation of "Share With Thy Neighbors: Single-View Reconstruction by Cross-Instance Consistency" pap
Implementation of the GVP-Transformer, which was used in the paper "Learning inverse folding from millions of predicted structures" for de novo protein design alongside Alphafold2
GVP Transformer (wip) Implementation of the GVP-Transformer, which was used in the paper Learning inverse folding from millions of predicted structure
Classification models 1D Zoo - Keras and TF.Keras
Classification models 1D Zoo - Keras and TF.Keras This repository contains 1D variants of popular CNN models for classification like ResNets, DenseNet
Semi-automated OpenVINO benchmark_app with variable parameters
Semi-automated OpenVINO benchmark_app with variable parameters. User can specify multiple options for any parameters in the benchmark_app and the progam runs the benchmark with all combinations of given options.
Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX.
snc4onnx Simple tool to combine(merge) onnx models. Simple Network Combine Tool for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools 1.
DeepGNN is a framework for training machine learning models on large scale graph data.
DeepGNN Overview DeepGNN is a framework for training machine learning models on large scale graph data. DeepGNN contains all the necessary features in
Implementation of MeMOT - Multi-Object Tracking with Memory - in Pytorch
MeMOT - Pytorch (wip) Implementation of MeMOT - Multi-Object Tracking with Memory - in Pytorch. This paper is just one in a line of work, but importan
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process
Aiming at the common training datsets split, spectrum preprocessing, wavelength select and calibration models algorithm involved in the spectral analysis process, a complete algorithm library is established, which is named opensa (openspectrum analysis).
A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for ONNX.
sam4onnx A very simple tool to rewrite parameters such as attributes and constants for OPs in ONNX models. Simple Attribute and Constant Modifier for
Simple ONNX operation generator. Simple Operation Generator for ONNX.
sog4onnx Simple ONNX operation generator. Simple Operation Generator for ONNX. https://github.com/PINTO0309/simple-onnx-processing-tools Key concept V
Simple node deletion tool for onnx.
snd4onnx Simple node deletion tool for onnx. I only test very miscellaneous and limited patterns as a hobby. There are probably a large number of bugs
PyTorch reimplementation of the Smooth ReLU activation function proposed in the paper "Real World Large Scale Recommendation Systems Reproducibility and Smooth Activations" [arXiv 2022].
Smooth ReLU in PyTorch Unofficial PyTorch reimplementation of the Smooth ReLU (SmeLU) activation function proposed in the paper Real World Large Scale
A library to inspect itermediate layers of PyTorch models.
A library to inspect itermediate layers of PyTorch models. Why? It's often the case that we want to inspect intermediate layers of a model without mod
一些经典的CTR算法的复现; LR, FM, FFM, AFM, DeepFM,xDeepFM, PNN, DCN, DCNv2, DIFM, AutoInt, FiBiNet,AFN,ONN,DIN, DIEN ... (pytorch, tf2.0)
CTR Algorithm 根据论文, 博客, 知乎等方式学习一些CTR相关的算法 理解原理并自己动手来实现一遍 pytorch & tf2.0 保持一颗学徒的心! Schedule Model pytorch tensorflow2.0 paper LR ✔️ ✔️ \ FM ✔️ ✔️ Fac
Helping data scientists better understand their datasets and models in text classification. With love from ServiceNow.
Azimuth, an open-source dataset and error analysis tool for text classification, with love from ServiceNow. Overview Azimuth is an open source applica
The official code of LM-Debugger, an interactive tool for inspection and intervention in transformer-based language models.
LM-Debugger is an open-source interactive tool for inspection and intervention in transformer-based language models. This repository includes the code
A very simple tool for situations where optimization with onnx-simplifier would exceed the Protocol Buffers upper file size limit of 2GB, or simply to separate onnx files to any size you want.
sne4onnx A very simple tool for situations where optimization with onnx-simplifier would exceed the Protocol Buffers upper file size limit of 2GB, or
Implementation of the Hybrid Perception Block and Dual-Pruned Self-Attention block from the ITTR paper for Image to Image Translation using Transformers
ITTR - Pytorch Implementation of the Hybrid Perception Block (HPB) and Dual-Pruned Self-Attention (DPSA) block from the ITTR paper for Image to Image
Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Retrieval.
Targeted Trojan-Horse Attacks on Language-based Image Retrieval Source code of our TTH paper: Targeted Trojan-Horse Attacks on Language-based Image Re
This repository contains the data and code for the paper "Diverse Text Generation via Variational Encoder-Decoder Models with Gaussian Process Priors" (SPNLP@ACL2022)
GP-VAE This repository provides datasets and code for preprocessing, training and testing models for the paper: Diverse Text Generation via Variationa
This is an open source library implementing hyperbox-based machine learning algorithms
hyperbox-brain is a Python open source toolbox implementing hyperbox-based machine learning algorithms built on top of scikit-learn and is distributed
Text classification is one of the popular tasks in NLP that allows a program to classify free-text documents based on pre-defined classes.
Deep-Learning-for-Text-Document-Classification Text classification is one of the popular tasks in NLP that allows a program to classify free-text docu
Athena is the only tool that you will ever need to optimize your portfolio.
Athena Portfolio optimization is the process of selecting the best portfolio (asset distribution), out of the set of all portfolios being considered,
Official repository of the paper Privacy-friendly Synthetic Data for the Development of Face Morphing Attack Detectors
SMDD-Synthetic-Face-Morphing-Attack-Detection-Development-dataset Official repository of the paper Privacy-friendly Synthetic Data for the Development
Bu repo SAHI uygulamasını mantığını öğreniyoruz.
SAHI-Learn: SAHI'den Beraber Kodlamak İster Misiniz Herkese merhabalar ben Kadir Nar. SAHI kütüphanesine gönüllü geliştiriciyim. Bu repo SAHI kütüphan
scAR (single-cell Ambient Remover) is a package for data denoising in single-cell omics.
scAR scAR (single cell Ambient Remover) is a package for denoising multiple single cell omics data. It can be used for multiple tasks, such as, sgRNA
PyTorch Implementation of "Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging" (Findings of ACL 2022)
Feature_CRF_AE Feature_CRF_AE provides a implementation of Bridging Pre-trained Language Models and Hand-crafted Features for Unsupervised POS Tagging
In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm was used to undersampling, SMOTEENN algorithm was applied as a combinatorial approach of over- and undersampling of credit card credit dataset from LendingClub. Machine learning models - BalancedRandomForestClassifier and EasyEnsembleClassifier were used to predict credit risk.
Overview of Credit Card Analysis In this project, RandomOverSampler and SMOTE algorithms were used to perform oversampling, ClusterCentroids algorithm
Under the hood working of transformers, fine-tuning GPT-3 models, DeBERTa, vision models, and the start of Metaverse, using a variety of NLP platforms: Hugging Face, OpenAI API, Trax, and AllenNLP
Transformers-for-NLP-2nd-Edition @copyright 2022, Packt Publishing, Denis Rothman Contact me for any question you have on LinkedIn Get the book on Ama
A deep learning CNN model to identify and classify and check if a person is wearing a mask or not.
Face Mask Detection The Model is designed to check if any human is wearing a mask or not. Dataset Description The Dataset contains a total of 11,792 i
[CVPR 2022] Official code for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved Neural Network Calibration"
MDCA Calibration This is the official PyTorch implementation for the paper: "A Stitch in Time Saves Nine: A Train-Time Regularizing Loss for Improved
Official implementation of Unfolded Deep Kernel Estimation for Blind Image Super-resolution.
Unfolded Deep Kernel Estimation for Blind Image Super-resolution Hongyi Zheng, Hongwei Yong, Lei Zhang, "Unfolded Deep Kernel Estimation for Blind Ima
Code base for "On-the-Fly Test-time Adaptation for Medical Image Segmentation"
On-the-Fly Adaptation Official Pytorch Code base for On-the-Fly Test-time Adaptation for Medical Image Segmentation Paper Introduction One major probl
This repository contains the code and models necessary to replicate the results of paper: How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M
Repository for "Improving evidential deep learning via multi-task learning," published in AAAI2022
Improving evidential deep learning via multi task learning It is a repository of AAAI2022 paper, “Improving evidential deep learning via multi-task le
Implementation of a memory efficient multi-head attention as proposed in the paper, "Self-attention Does Not Need O(n²) Memory"
Memory Efficient Attention Pytorch Implementation of a memory efficient multi-head attention as proposed in the paper, Self-attention Does Not Need O(
Comparison-of-OCR (KerasOCR, PyTesseract,EasyOCR)
Optical Character Recognition OCR (Optical Character Recognition) is a technology that enables the conversion of document types such as scanned paper
This repository contains the code and models necessary to replicate the results of paper: How to Robustify Black-Box ML Models? A Zeroth-Order Optimization Perspective
Black-Box-Defense This repository contains the code and models necessary to replicate the results of our recent paper: How to Robustify Black-Box ML M
Input english text, then translate it between languages n times using the Deep Translator Python Library.
mass-translator About Input english text, then translate it between languages n times using the Deep Translator Python Library. How to Use Install dep
Experimental Python implementation of OpenVINO Inference Engine (very slow, limited functionality). All codes are written in Python. Easy to read and modify.
PyOpenVINO - An Experimental Python Implementation of OpenVINO Inference Engine (minimum-set) Description The PyOpenVINO is a spin-off product from my
PyTorch Implementation of DiffGAN-TTS: High-Fidelity and Efficient Text-to-Speech with Denoising Diffusion GANs
DiffGAN-TTS - PyTorch Implementation PyTorch implementation of DiffGAN-TTS: High
Neural-Machine-Translation - Implementation of revolutionary machine translation models
Neural Machine Translation Framework: PyTorch Repository contaning my implementa
Covid19-Forecasting - An interactive website that tracks, models and predicts COVID-19 Cases
Covid-Tracker This is an interactive website that tracks, models and predicts CO
DLWP: Deep Learning Weather Prediction
DLWP: Deep Learning Weather Prediction DLWP is a Python project containing data-
Autolfads-tf2 - A TensorFlow 2.0 implementation of Latent Factor Analysis via Dynamical Systems (LFADS) and AutoLFADS
autolfads-tf2 A TensorFlow 2.0 implementation of LFADS and AutoLFADS. Installati
Job-Recommend-Competition - Vectorwise Interpretable Attentions for Multimodal Tabular Data
SiD - Simple Deep Model Vectorwise Interpretable Attentions for Multimodal Tabul
Federated Learning - Including common test models for federated learning, like CNN, Resnet18 and lstm, controlled by different parser
Federated_Learning 💻 This projest include common test models for federated lear
LotteryBuyPredictionWebApp - Lottery Purchase Prediction Model
Lottery Purchase Prediction Model Objective and Goal Predict the lottery type th
Using PyTorch Perform intent classification using three different models to see which one is better for this task
Using PyTorch Perform intent classification using three different models to see which one is better for this task
OpenDelta - An Open-Source Framework for Paramter Efficient Tuning.
OpenDelta is a toolkit for parameter efficient methods (we dub it as delta tuning), by which users could flexibly assign (or add) a small amount parameters to update while keeping the most paramters frozen. By using OpenDelta, users could easily implement prefix-tuning, adapters, Lora, or any other types of delta tuning with preferred PTMs.
Detecting drunk people through thermal images using Deep Learning (CNN)
Drunk Detection CNN Detecting drunk people through thermal images using Deep Learning (CNN) Dataset We used thermal images provided by Electronics Lab
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation
RIFE - Real-Time Intermediate Flow Estimation for Video Frame Interpolation YouTube | BiliBili 16X interpolation results from two input images: Introd
icepickle is to allow a safe way to serialize and deserialize linear scikit-learn models
icepickle It's a cooler way to store simple linear models. The goal of icepickle is to allow a safe way to serialize and deserialize linear scikit-lea
The visual framework is designed on the idea of module and implemented by mixin method
Visual Framework The visual framework is designed on the idea of module and implemented by mixin method. Its biggest feature is the mixins module whic
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework
OpenFed: A Comprehensive and Versatile Open-Source Federated Learning Framework Introduction OpenFed is a foundational library for federated learning
PyTorch implementation for the paper Pseudo Numerical Methods for Diffusion Models on Manifolds
Pseudo Numerical Methods for Diffusion Models on Manifolds (PNDM) This repo is the official PyTorch implementation for the paper Pseudo Numerical Meth
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
An open software package to develop BCI based brain and cognitive computing technology for recognizing user's intention using deep learning
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL)
Locally Differentially Private Distributed Deep Learning via Knowledge Distillation (LDP-DL) A preprint version of our paper: Link here This is a samp
Code To Tune or Not To Tune? Zero-shot Models for Legal Case Entailment.
COLIEE 2021 - task 2: Legal Case Entailment This repository contains the code to reproduce NeuralMind's submissions to COLIEE 2021 presented in the pa
Source code of our work: "Benchmarking Deep Models for Salient Object Detection"
SALOD Source code of our work: "Benchmarking Deep Models for Salient Object Detection". In this works, we propose a new benchmark for SALient Object D
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors
CZU-MHAD: A multimodal dataset for human action recognition utilizing a depth camera and 10 wearable inertial sensors In order to facilitate the res
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences
Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences This repository is an official PyTorch implementation of Neighbor
Using deep learning model to detect breast cancer.
Breast-Cancer-Detection Breast cancer is the most frequent cancer among women, with around one in every 19 women at risk. The number of cases of breas
A python package to fine-tune transformer-based models for named entity recognition (NER).
nerblackbox A python package to fine-tune transformer-based language models for named entity recognition (NER). Resources Source Code: https://github.
Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable.
Diffrax Numerical differential equation solvers in JAX. Autodifferentiable and GPU-capable. Diffrax is a JAX-based library providing numerical differe
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
This is the replication package for paper submission: Towards Training Reproducible Deep Learning Models.
Convert BART models to ONNX with quantization. 3X reduction in size, and upto 3X boost in inference speed
fast-Bart Reduction of BART model size by 3X, and boost in inference speed up to 3X BART implementation of the fastT5 library (https://github.com/Ki6a
KoRean based ELECTRA pre-trained models (KR-ELECTRA) for Tensorflow and PyTorch
KoRean based ELECTRA (KR-ELECTRA) This is a release of a Korean-specific ELECTRA model with comparable or better performances developed by the Computa
EquiBind: Geometric Deep Learning for Drug Binding Structure Prediction
EquiBind: geometric deep learning for fast predictions of the 3D structure in which a small molecule binds to a protein
Non-Autoregressive Translation with Layer-Wise Prediction and Deep Supervision
Deeply Supervised, Layer-wise Prediction-aware (DSLP) Transformer for Non-autoregressive Neural Machine Translation