7173 Repositories
Python SUPERVISED-CONTRASTIVE-LEARNING-FOR-PRE-TRAINED-LANGUAGE-MODEL-FINE-TUNING Libraries
Byzantine-robust decentralized learning via self-centered clipping
Byzantine-robust decentralized learning via self-centered clipping In this paper, we study the challenging task of Byzantine-robust decentralized trai
FedGS: A Federated Group Synchronization Framework Implemented by LEAF-MX.
FedGS: Data Heterogeneity-Robust Federated Learning via Group Client Selection in Industrial IoT Preparation For instructions on generating data, plea
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
L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources.
L3Cube-MahaCorpus L3Cube-MahaCorpus a Marathi monolingual data set scraped from different internet sources. We expand the existing Marathi monolingual
Python package for concise, transparent, and accurate predictive modeling
Python package for concise, transparent, and accurate predictive modeling. All sklearn-compatible and easy to use. 📚 docs • 📖 demo notebooks Modern
Towards Representation Learning for Atmospheric Dynamics (AtmoDist)
Towards Representation Learning for Atmospheric Dynamics (AtmoDist) The prediction of future climate scenarios under anthropogenic forcing is critical
Multi-Task Learning as a Bargaining Game.
Nash-MTL Official implementation of "Multi-Task Learning as a Bargaining Game". Setup environment conda create -n nashmtl python=3.9.7 conda activate
Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionaries
Dictionary Learning for Clustering on Hyperspectral Images Overview Framework for Spectral Clustering on the Sparse Coefficients of Learned Dictionari
Efficient Deep Learning Systems course
Efficient Deep Learning Systems This repository contains materials for the Efficient Deep Learning Systems course taught at the Faculty of Computer Sc
Deep Learning agent of Starcraft2, similar to AlphaStar of DeepMind except size of network.
Introduction This repository is for Deep Learning agent of Starcraft2. It is very similar to AlphaStar of DeepMind except size of network. I only test
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.
Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions"
Graph Convolution Simulator (GCS) Source code for "Understanding Knowledge Integration in Language Models with Graph Convolutions" Requirements: PyTor
Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties
Element selection for functional materials discovery by integrated machine learning of atomic contributions to properties 8.11.2021 Andrij Vasylenko I
A repo for Causal Imitation Learning under Temporally Correlated Noise
CausIL A repo for Causal Imitation Learning under Temporally Correlated Noise. Running Experiments To re-train an expert, run: python experts/train_ex
CodeContests is a competitive programming dataset for machine-learning
CodeContests CodeContests is a competitive programming dataset for machine-learning. This dataset was used when training AlphaCode. It consists of pro
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
LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs.
LocUNet LocUNet is a deep learning method to localize a UE based solely on the reported signal strengths from a set of BSs. The method utilizes accura
A Learning-based Camera Calibration Toolbox
Learning-based Camera Calibration A Learning-based Camera Calibration Toolbox Paper The pdf file can be found here. @misc{zhang2022learningbased,
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
FewBit — a library for memory efficient training of large neural networks
FewBit FewBit — a library for memory efficient training of large neural networks. Its efficiency originates from storage optimizations applied to back
This repository is the code of the paper Accelerating Deep Reinforcement Learning for Digital Twin Network Optimization with Evolutionary Strategies
ES_OTN_Public Carlos GĂĽemes Palau, Paul Almasan, Pere Barlet Ros, Albert Cabellos Aparicio Contact us: [email protected], contactus@bn
Meta-meta-learning with evolution and plasticity
Evolve plastic networks to be able to automatically acquire novel cognitive (meta-learning) tasks
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
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
Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies
py-self-organizing-map Simple implementation of Self Organizing Maps (SOMs) with rectangular and hexagonal grid topologies. A SOM is a simple unsuperv
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] [
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition
MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition Paper: MinkLoc++: Lidar and Monocular Image Fusion for Place Recognition accepted fo
DiffStride: Learning strides in convolutional neural networks
DiffStride is a pooling layer with learnable strides. Unlike strided convolutions, average pooling or max-pooling that require cross-validating stride values at each layer, DiffStride can be initialized with an arbitrary value at each layer (e.g. (2, 2) and during training its strides will be optimized for the task at hand.
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
This repository contains the implementation of the paper Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans
Contrastive Instance Association for 4D Panoptic Segmentation using Sequences of 3D LiDAR Scans This repository contains the implementation of the pap
Recommender systems are the systems that are designed to recommend things to the user based on many different factors
Recommender systems are the systems that are designed to recommend things to the user based on many different factors. The recommender system deals with a large volume of information present by filtering the most important information based on the data provided by a user and other factors that take care of the user’s preference and interest.
Trafffic prediction analysis using hybrid models - Machine Learning
Hybrid Machine learning Model Clone the Repository Create a new Directory as assests and download the model from the below link Model Link To Start th
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
SeisComP/SeisBench interface to enable deep-learning (re)picking in SeisComP
scdlpicker SeisComP/SeisBench interface to enable deep-learning (re)picking in SeisComP Objective This is a simple deep learning (DL) repicker module
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.
CT Based COVID 19 Diagnose by Image Processing and Deep Learning
This project proposed the deep learning and image processing method to undertake the diagnosis on 2D CT image and 3D CT volume.
Earthquake detection via fiber optic cables using deep learning
Earthquake detection via fiber optic cables using deep learning Author: Fantine Huot Getting started Update the submodules After cloning the repositor
Implementation of the method described in the Speech Resynthesis from Discrete Disentangled Self-Supervised Representations.
Speech Resynthesis from Discrete Disentangled Self-Supervised Representations Implementation of the method described in the Speech Resynthesis from Di
Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5
NLP-Summarizer Natural language processing summarizer using 3 state of the art Transformer models: BERT, GPT2, and T5 This project aimed to provide in
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 stack-based systems language that supports structures, functions, expressions, and user-defined operator behaviour
A stack-based systems language that supports structures, functions, expressions, and user-defined operator behaviour. Currently compiles to URCL with plans to add additional formats in the future.
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
Open source simulator for autonomous vehicles built on Unreal Engine / Unity, from Microsoft AI & Research
Welcome to AirSim AirSim is a simulator for drones, cars and more, built on Unreal Engine (we now also have an experimental Unity release). It is open
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.
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc)
Built various Machine Learning algorithms (Logistic Regression, Random Forest, KNN, Gradient Boosting and XGBoost. etc). Structured a custom ensemble model and a neural network. Found a outperformed model for heart failure prediction accuracy of 88 percent.
A simple assembly- and brainfuck-inspired stack-based language
asm-stackfuck A simple assembly- and brainfuck-inspired stack-based language. The language has a few goals: Be stack-based Look like assembly Have a s
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification
Temporal Alignment Prediction for Supervised Representation Learning and Few-Shot Sequence Classification Introduction. This package includes the pyth
A web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks
This project is a web porting for NVlabs' StyleGAN2, to facilitate exploring all kinds characteristic of StyleGAN networks. Thanks for NVlabs' excelle
Generate Cartoon Images using Generative Adversarial Network
AvatarGAN ✨ Generate Cartoon Images using DC-GAN Deep Convolutional GAN is a generative adversarial network architecture. It uses a couple of guidelin
A list of Machine Learning Art Colabs
ML Visual Art Colabs A list of cool Colabs on Machine Learning Imagemaking or other artistic purposes 3D Ken Burns Effect Ken Burns Effect by Manuel R
A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution.
Awesome Pretrained StyleGAN2 A collection of pre-trained StyleGAN2 models trained on different datasets at different resolution. Note the readme is a
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
A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook format ready to run in Google Colaboratory
Awesome Machine Learning Jupyter Notebooks for Google Colaboratory A curated list of Machine Learning and Deep Learning tutorials in Jupyter Notebook
Helperpod - A CLI tool to run a Kubernetes utility pod with pre-installed tools that can be used for debugging/testing purposes inside a Kubernetes cluster
Helperpod is a CLI tool to run a Kubernetes utility pod with pre-installed tools that can be used for debugging/testing purposes inside a Kubernetes cluster.
Reso is a low-level circuit design language and simulator, inspired by things like Redstone, Conway's Game of Life, and Wireworld.
Reso Reso is a low-level circuit design language and simulator, inspired by things like Redstone, Conway's Game of Life, and Wireworld. What is Reso?
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
Semantic Segmentation Architectures Implemented in PyTorch
pytorch-semseg Semantic Segmentation Algorithms Implemented in PyTorch This repository aims at mirroring popular semantic segmentation architectures i
Semantic Segmentation Suite in TensorFlow
Semantic Segmentation Suite in TensorFlow. Implement, train, and test new Semantic Segmentation models easily!
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
Example of semantic segmentation in Keras
keras-semantic-segmentation-example Example of semantic segmentation in Keras Single class example: Generated data: random ellipse with random color o
RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network trained to work with different pairs (images, texts).
RuCLIPtiny Zero-shot image classification model for Russian language RuCLIP tiny (Russian Contrastive Language–Image Pretraining) is a neural network
YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600Ă—600 pixel size typically ingested by deep learning object detection frameworks
YOLTv5 rapidly detects objects in arbitrarily large aerial or satellite images that far exceed the ~600Ă—600 pixel size typically ingested by deep learning object detection frameworks.
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
Natural Language Processing at EDHEC, 2022
Natural Language Processing Here you will find the teaching materials for the "Natural Language Processing" course at EDHEC Business School, 2022 What
Machine learning classifiers to predict American Sign Language .
ASL-Classifiers American Sign Language (ASL) is a natural language that serves as the predominant sign language of Deaf communities in the United Stat
Drslmarkov - Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
Distributionally Robust Structure Learning for Discrete Pairwise Markov Networks
VOS: Learning What You Don’t Know by Virtual Outlier Synthesis
VOS This is the source code accompanying the paper VOS: Learning What You Don’t
Bert4rec for news Recommendation
News-Recommendation-system-using-Bert4Rec-model Bert4rec for news Recommendation
Builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques
This project builds a LoRa radio frequency fingerprint identification (RFFI) system based on deep learning techiniques.
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.
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
Python Assignments for the Deep Learning lectures by Andrew NG on coursera with complete submission for grading capability.
Implementation of the SUMO (Slim U-Net trained on MODA) model
SUMO - Slim U-Net trained on MODA Implementation of the SUMO (Slim U-Net trained on MODA) model as described in: TODO: add reference to paper once ava
SuperSonic, a new open-source framework to allow compiler developers to integrate RL into compilers easily, regardless of their RL expertise
Automating reinforcement learning architecture design for code optimization. Che
vimBrain is a brainfuck-based vim-inspired esoteric programming language.
vimBrain vimBrain is a brainfuck-based vim-inspired esoteric programming language. vimBrainPy Currently, the only interpreter available is written in
Mae segmentation - Reproduction of semantic segmentation using masked autoencoder (mae)
ADE20k Semantic segmentation with MAE Getting started Install the mmsegmentation
Training a deep learning model on the noisy CIFAR dataset
Training-a-deep-learning-model-on-the-noisy-CIFAR-dataset This repository contai
Machine Learning Models were applied to predict the mass of the brain based on gender, age ranges, and head size.
Brain Weight in Humans Variations of head sizes and brain weights in humans Kaggle dataset obtained from this link by Anubhab Swain. Image obtained fr
A machine learning model for Covid case prediction
CovidcasePrediction A machine learning model for Covid case prediction Problem Statement Using regression algorithms we can able to track the active c
This project is an open-source project which I made due to sharing my experience around the Python programming language.
django-tutorial This project is an open-source project which I made due to sharing my experience around the Django framework. What is Django? Django i
A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM's
sign-language-detection A Sign Language detection project using Mediapipe landmark detection and Tensorflow LSTM. The project is built for a vocabular
GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates
GraphNLI: A Graph-based Natural Language Inference Model for Polarity Prediction in Online Debates Vibhor Agarwal, Sagar Joglekar, Anthony P. Young an
Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning
Harmonious Textual Layout Generation over Natural Images via Deep Aesthetics Learning Code for the paper Harmonious Textual Layout Generation over Nat
PyTorch implementation of DirectCLR from paper Understanding Dimensional Collapse in Contrastive Self-supervised Learning
DirectCLR DirectCLR is a simple contrastive learning model for visual representation learning. It does not require a trainable projector as SimCLR. It
This repository contains the entire code for our work "Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding"
Two-Timescale-DNN Two-Timescale End-to-End Learning for Channel Acquisition and Hybrid Precoding This repository contains the entire code for our work
The aim is to extract timeseries water level 2D information for any designed boundaries within the EasyGSH model domain
bct_file_generator_for_EasyGSH The aim is to extract timeseries water level 2D information for any designed boundaries within the EasyGSH model domain
Convert monolithic Jupyter notebooks into Ploomber pipelines.
Soorgeon Join our community | Newsletter | Contact us | Blog | Website | YouTube Convert monolithic Jupyter notebooks into Ploomber pipelines. soorgeo
The NewSHead dataset is a multi-doc headline dataset used in NHNet for training a headline summarization model.
This repository contains the raw dataset used in NHNet [1] for the task of News Story Headline Generation. The code of data processing and training is available under Tensorflow Models - NHNet.
This repository collects together basic linguistic processing data for using dataset dumps from the Common Voice project
Common Voice Utils This repository collects together basic linguistic processing data for using dataset dumps from the Common Voice project. It aims t
This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize over continuous domains by Brandon Amos
Tutorial on Amortized Optimization This repository contains the source code for the paper Tutorial on amortized optimization for learning to optimize
Constrained Language Models Yield Few-Shot Semantic Parsers
Constrained Language Models Yield Few-Shot Semantic Parsers This repository contains tools and instructions for reproducing the experiments in the pap