4004 Repositories
Python PyTorch-Model-Compare Libraries
SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING - The Facebook paper about fine tuning RoBERTa with contrastive loss
"# SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING" i
LotteryBuyPredictionWebApp - Lottery Purchase Prediction Model
Lottery Purchase Prediction Model Objective and Goal Predict the lottery type th
Sharpened cosine similarity torch - A Sharpened Cosine Similarity layer for PyTorch
Sharpened Cosine Similarity A layer implementation for PyTorch Install At your c
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.
A model to predict steering torque fully end-to-end
torque_model The torque model is a spiritual successor to op-smart-torque, which was a project to train a neural network to control a car's steering f
This is the code repository for LRM Stochastic watershed model.
LRM-Squannacook Input data for generating stochastic streamflows are observed and simulated timeseries of streamflow. their format needs to be CSV wit
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
Over-the-Air Ensemble Inference with Model Privacy
Over-the-Air Ensemble Inference with Model Privacy This repository contains simulations for our private ensemble inference method. Installation Instal
PyTorch implementation of the Crafting Better Contrastive Views for Siamese Representation Learning
Crafting Better Contrastive Views for Siamese Representation Learning This is the official PyTorch implementation of the ContrastiveCrop paper: @artic
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
PyTorch implementation of NATSpeech: A Non-Autoregressive Text-to-Speech Framework
A Non-Autoregressive Text-to-Speech (NAR-TTS) framework, including official PyTorch implementation of PortaSpeech (NeurIPS 2021) and DiffSpeech (AAAI 2022)
ONNX-PackNet-SfM: Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX
Python scripts for performing monocular depth estimation using the PackNet-SfM model in ONNX
Brain tumor detection using CNN (InceptionResNetV2 Model)
Brain-Tumor-Detection Building a detection model using a convolutional neural network in Tensorflow & Keras. Used brain MRI images. InceptionResNetV2
3D Model files and source code for rotating turntable. Raspberry Pi, DC servo and PWM modulator required.
3DSimpleTurntable 3D Model files and source code for rotating turntable. Raspberry Pi, DC servo and PWM modulator required. Preview Construction Print
Learned model to estimate number of distinct values (NDV) of a population using a small sample.
Learned NDV estimator Learned model to estimate number of distinct values (NDV) of a population using a small sample. The model approximates the maxim
PyTorch-Geometric Implementation of MarkovGNN: Graph Neural Networks on Markov Diffusion
MarkovGNN This is the official PyTorch-Geometric implementation of MarkovGNN paper under the title "MarkovGNN: Graph Neural Networks on Markov Diffusi
This repository contains the code for: RerrFact model for SciVer shared task
RerrFact This repository contains the code for: RerrFact model for SciVer shared task. Setup for Inference 1. Download SciFact database Download the S
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder
Memory Defense: More Robust Classificationvia a Memory-Masking Autoencoder Authors: - Eashan Adhikarla - Dan Luo - Dr. Brian D. Davison Abstract Many
Citation Intent Classification in scientific papers using the Scicite dataset an Pytorch
Citation Intent Classification Table of Contents About the Project Built With Installation Usage Acknowledgments About The Project Citation Intent Cla
PyTorch-lightning implementation of the ESFW module proposed in our paper Edge-Selective Feature Weaving for Point Cloud Matching
Edge-Selective Feature Weaving for Point Cloud Matching This repository contains a PyTorch-lightning implementation of the ESFW module proposed in our
Implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networks, using PyTorch
C-CNN: Contourlet Convolutional Neural Networks This repo implemenets the Contourlet-CNN as described in C-CNN: Contourlet Convolutional Neural Networ
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
PyTorch implementation for NCL (Neighborhood-enrighed Contrastive Learning)
NCL (Neighborhood-enrighed Contrastive Learning) This is the official PyTorch implementation for the paper: Zihan Lin*, Changxin Tian*, Yupeng Hou* Wa
A pure PyTorch batched computation implementation of "CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition"
A pure PyTorch batched computation implementation of "CIF: Continuous Integrate-and-Fire for End-to-End Speech Recognition"
FNet Implementation with TensorFlow & PyTorch
FNet Implementation with TensorFlow & PyTorch. TensorFlow & PyTorch implementation of the paper "FNet: Mixing Tokens with Fourier Transforms". Overvie
Image-to-image regression with uncertainty quantification in PyTorch
Image-to-image regression with uncertainty quantification in PyTorch. Take any dataset and train a model to regress images to images with rigorous, distribution-free uncertainty quantification.
Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations
TopClus The source code used for Topic Discovery via Latent Space Clustering of Pretrained Language Model Representations, published in WWW 2022. Requ
BASH - Biomechanical Animated Skinned Human
We developed a method animating a statistical 3D human model for biomechanical analysis to increase accessibility for non-experts, like patients, athletes, or designers.
PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation
PyTorch Implementation of our paper Explain Me the Painting: Multi-Topic Knowledgeable Art Description Generation
BROS: A Pre-trained Language Model Focusing on Text and Layout for Better Key Information Extraction from Documents
BROS (BERT Relying On Spatiality) is a pre-trained language model focusing on text and layout for better key information extraction from documents. Given the OCR results of the document image, which are text and bounding box pairs, it can perform various key information extraction tasks, such as extracting an ordered item list from receipts
Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection
DDMP-3D Pytorch implementation of Depth-conditioned Dynamic Message Propagation forMonocular 3D Object Detection, a paper on CVPR2021. Instroduction T
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection?
PyTorch implementation of DD3D: Is Pseudo-Lidar needed for Monocular 3D Object detection? (ICCV 2021), Dennis Park*, Rares Ambrus*, Vitor Guizilini, Jie Li, and Adrien Gaidon.
PyTorch implementations of the NeRF model described in "NeRF: Representing Scenes as Neural Radiance Fields for View Synthesis"
PyTorch NeRF and pixelNeRF NeRF: Tiny NeRF: pixelNeRF: This repository contains minimal PyTorch implementations of the NeRF model described in "NeRF:
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
Price Prediction model is used to develop an LSTM model to predict the future market price of Bitcoin and Ethereum.
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning"
PyTorch Implementation of the SuRP algorithm by the authors of the AISTATS 2022 paper "An Information-Theoretic Justification for Model Pruning".
To build a regression model to predict the concrete compressive strength based on the different features in the training data.
Cement-Strength-Prediction Problem Statement To build a regression model to predict the concrete compressive strength based on the different features
Artificial Neural network regression model to predict the energy output in a combined cycle power plant.
Energy_Output_Predictor Artificial Neural network regression model to predict the energy output in a combined cycle power plant. Abstract Energy outpu
Neural Radiance Fields Using PyTorch
This project is a PyTorch implementation of Neural Radiance Fields (NeRF) for reproduction of results whilst running at a faster speed.
A custom DeepStack model that has been trained detecting ONLY the USPS logo
This repository provides a custom DeepStack model that has been trained detecting ONLY the USPS logo. This was created after I discovered that the Deepstack OpenLogo custom model I was using did not contain USPS.
KinectFusion implemented in Python with PyTorch
KinectFusion implemented in Python with PyTorch This is a lightweight Python implementation of KinectFusion. All the core functions (TSDF volume, fram
Rank-One Model Editing for Locating and Editing Factual Knowledge in GPT
Rank-One Model Editing (ROME) This repository provides an implementation of Rank-One Model Editing (ROME) on auto-regressive transformers (GPU-only).
PyTorch implementation of SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching
SMODICE: Versatile Offline Imitation Learning via State Occupancy Matching This is the official PyTorch implementation of SMODICE: Versatile Offline I
NeuroGen: activation optimized image synthesis for discovery neuroscience
NeuroGen: activation optimized image synthesis for discovery neuroscience NeuroGen is a framework for synthesizing images that control brain activatio
PyTorch implementation of the ExORL: Exploratory Data for Offline Reinforcement Learning
ExORL: Exploratory Data for Offline Reinforcement Learning This is an original PyTorch implementation of the ExORL framework from Don't Change the Alg
Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels without Knowing Noise Rates"
Peer Loss functions This repository is the (Multi-Class & Deep Learning) Pytorch implementation of "Peer Loss Functions: Learning from Noisy Labels wi
CBO uses its Capital Tax model (CBO-CapTax) to estimate the effects of federal taxes on capital income from new investment
CBO’s CapTax Model CBO uses its Capital Tax model (CBO-CapTax) to estimate the effects of federal taxes on capital income from new investment. Specifi
The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding.
SuperGen The source code for Generating Training Data with Language Models: Towards Zero-Shot Language Understanding. Requirements Before running, you
Pytorch implementation of MaskGIT: Masked Generative Image Transformer
Pytorch implementation of MaskGIT: Masked Generative Image Transformer
Easily benchmark PyTorch model FLOPs, latency, throughput, max allocated memory and energy consumption
⏱ pytorch-benchmark Easily benchmark model inference FLOPs, latency, throughput, max allocated memory and energy consumption Install pip install pytor
Customised to detect objects automatically by a given model file(onnx)
LabelImg LabelImg is a graphical image annotation tool. It is written in Python and uses Qt for its graphical interface. Annotations are saved as XML
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model About This repository contains the code to replicate the syn
PyTorch implementation of the paper: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features
Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features Estimate the noise transition matrix with f-mutual information. This co
The mini-AlphaStar (mini-AS, or mAS) - mini-scale version (non-official) of the AlphaStar (AS)
A mini-scale reproduction code of the AlphaStar program. Note: the original AlphaStar is the AI proposed by DeepMind to play StarCraft II.
Nested cross-validation is necessary to avoid biased model performance in embedded feature selection in high-dimensional data with tiny sample sizes
Pruner for nested cross-validation - Sphinx-Doc Nested cross-validation is necessary to avoid biased model performance in embedded feature selection i
This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive Selective Coding)
HCSC: Hierarchical Contrastive Selective Coding This repository provides a PyTorch implementation and model weights for HCSC (Hierarchical Contrastive
A model which classifies reviews as positive or negative.
SentiMent Analysis In this project I built a model to classify movie reviews fromn the IMDB dataset of 50K reviews. WordtoVec : Neural networks only w
Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020.
RegNet Pytorch Implementation of "Desigining Network Design Spaces", Radosavovic et al. CVPR 2020. Paper | Official Implementation RegNet offer a very
Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron
Convert Pytorch model to onnx or tflite, and the converted model can be visualized by Netron
Pytorch Implementation for Dilated Continuous Random Field
DilatedCRF Pytorch implementation for fully-learnable DilatedCRF. If you find my work helpful, please consider our paper: @article{Mo2022dilatedcrf,
Pytorch implementation of TailCalibX : Feature Generation for Long-tail Classification
TailCalibX : Feature Generation for Long-tail Classification by Rahul Vigneswaran, Marc T. Law, Vineeth N. Balasubramanian, Makarand Tapaswi [arXiv] [
ElasticFace: Elastic Margin Loss for Deep Face Recognition
This is the official repository of the paper: ElasticFace: Elastic Margin Loss for Deep Face Recognition Paper on arxiv: arxiv Model Log file Pretrain
Official PyTorch implementation of the NeurIPS 2021 paper StyleGAN3
Alias-Free Generative Adversarial Networks (StyleGAN3) Official PyTorch implementation of the NeurIPS 2021 paper Alias-Free Generative Adversarial Net
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)"
Official PyTorch implementation of the paper "Likelihood Training of Schrödinger Bridge using Forward-Backward SDEs Theory (SB-FBSDE)" which introduces a new class of deep generative models that generalizes score-based models to fully nonlinear forward and backward diffusions.
This repository provides an efficient PyTorch-based library for training deep models.
An Efficient Library for Training Deep Models This repository provides an efficient PyTorch-based library for training deep models. Installation Make
This code is the implementation of Text Emotion Recognition (TER) with linguistic features
APSIPA-TER This code is the implementation of Text Emotion Recognition (TER) with linguistic features. The network model is BERT with a pretrained mod
Speech Emotion Recognition with Fusion of Acoustic- and Linguistic-Feature-Based Decisions
APSIPA-SER-with-A-and-T This code is the implementation of Speech Emotion Recognition (SER) with acoustic and linguistic features. The network model i
NeuralForecast is a Python library for time series forecasting with deep learning models
NeuralForecast is a Python library for time series forecasting with deep learning models. It includes benchmark datasets, data-loading utilities, evaluation functions, statistical tests, univariate model benchmarks and SOTA models implemented in PyTorch and PyTorchLightning.
To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.
To create a deep learning model which can explain the content of an image in the form of speech through caption generation with attention mechanism on Flickr8K dataset.
A pure PyTorch implementation of the loss described in "Online Segment to Segment Neural Transduction"
ssnt-loss ℹ️ This is a WIP project. the implementation is still being tested. A pure PyTorch implementation of the loss described in "Online Segment t
Sequence-tagging using deep learning
Classification using Deep Learning Requirements PyTorch version = 1.9.1+cu111 Python version = 3.8.10 PyTorch-Lightning version = 1.4.9 Huggingface
A simple tutoral for error correction task, based on Pytorch
gramcorrector A simple tutoral for error correction task, based on Pytorch Grammatical Error Detection (sentence-level) a binary sequence-based classi
CRF-RNN for Semantic Image Segmentation - PyTorch version
This repository contains the official PyTorch implementation of the "CRF-RNN" semantic image segmentation method, published in the ICCV 2015
Python inverse kinematics for your robot model based on Pinocchio.
Python inverse kinematics for your robot model based on Pinocchio.
An implementation of IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification
IMLE-Net: An Interpretable Multi-level Multi-channel Model for ECG Classification The repostiory consists of the code, results and data set links for
This machine learning model was developed for House Prices
This machine learning model was developed for House Prices - Advanced Regression Techniques competition in Kaggle by using several machine learning models such as Random Forest, XGBoost and LightGBM.
Official PyTorch implementation of StyleGAN3
Modified StyleGAN3 Repo Changes Made tied to python 3.7 syntax .jpgs instead of .pngs for training sample seeds to recreate the 1024 training grid wit
Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included.
pixel_character_generator Generating retro pixel game characters with Generative Adversarial Networks. Dataset "TinyHero" included. Dataset TinyHero D
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries.
The unified machine learning framework, enabling framework-agnostic functions, layers and libraries. Contents Overview In a Nutshell Where Next? Overv
A PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detection.
R-YOLOv4 This is a PyTorch-based R-YOLOv4 implementation which combines YOLOv4 model and loss function from R3Det for arbitrary oriented object detect
ONNX-GLPDepth - Python scripts for performing monocular depth estimation using the GLPDepth model in ONNX
ONNX-GLPDepth - Python scripts for performing monocular depth estimation using the GLPDepth model in ONNX
Torch-mutable-modules - Use in-place and assignment operations on PyTorch module parameters with support for autograd
Torch Mutable Modules Use in-place and assignment operations on PyTorch module p
Pytorch implementation of OCNet series and SegFix.
openseg.pytorch News 2021/09/14 MMSegmentation has supported our ISANet and refer to ISANet for more details. 2021/08/13 We have released the implemen
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Evaluation framework for testing segmentation networks in PyTorch
Evaluation framework for testing segmentation networks in PyTorch. What segmentation network to choose for next Kaggle competition? This benchmark knows the answer!
Image Segmentation and Object Detection in Pytorch
Image Segmentation and Object Detection in Pytorch Pytorch-Segmentation-Detection is a library for image segmentation and object detection with report
This project aims at providing a concise, easy-to-use, modifiable reference implementation for semantic segmentation models using PyTorch.
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
Human segmentation models, training/inference code, and trained weights, implemented in PyTorch
Human-Segmentation-PyTorch Human segmentation models, training/inference code, and trained weights, implemented in PyTorch. Supported networks UNet: b
Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"
Pytorch implementation of the paper "Enhancing Content Preservation in Text Style Transfer Using Reverse Attention and Conditional Layer Normalization"
Evaluate on three different ML model for feature selection using Breast cancer data.
Anomaly-detection-Feature-Selection Evaluate on three different ML model for feature selection using Breast cancer data. ML models: SVM, KNN and MLP.
Breast cancer is been classified into benign tumour and malignant tumour.
Breast cancer is been classified into benign tumour and malignant tumour. Logistic regression is applied in this model.
Breast Cancer Classification Model is applied on a different dataset
Breast Cancer Classification Model is applied on a different dataset
ANN model for prediction a spatio-temporal distribution of supercooled liquid in mixed-phase clouds using Doppler cloud radar spectra.
VOODOO Revealing supercooled liquid beyond lidar attenuation Explore the docs » Report Bug · Request Feature Table of Contents About The Project Built
SAAVN - Sound Adversarial Audio-Visual Navigation,ICLR2022 (In PyTorch)
SAAVN SAAVN Code release for paper "Sound Adversarial Audio-Visual Navigation,IC
Bert4rec for news Recommendation
News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation
Pytorch implementation of various High Dynamic Range (HDR) Imaging algorithms
Deep High Dynamic Range Imaging Benchmark This repository is the pytorch impleme
Sub-tomogram-Detection - Deep learning based model for Cyro ET Sub-tomogram-Detection
Deep learning based model for Cyro ET Sub-tomogram-Detection High degree of stru
This is a model made out of Neural Network specifically a Convolutional Neural Network model
This is a model made out of Neural Network specifically a Convolutional Neural Network model. This was done with a pre-built dataset from the tensorflow and keras packages. There are other alternative libraries that can be used for this purpose, one of which is the PyTorch library.