9397 Repositories
Python Sentiment-analysis-using-XLnet-Deep-learning-in-natural-language-processing- Libraries
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees
ResNEsts and DenseNEsts: Block-based DNN Models with Improved Representation Guarantees This repository is the official implementation of the empirica
K-means clustering is a method used for clustering analysis, especially in data mining and statistics.
K Means Algorithm What is K Means This algorithm is an iterative algorithm that partitions the dataset according to their features into K number of pr
Space Time Recurrent Memory Network - Pytorch
Space Time Recurrent Memory Network - Pytorch (wip) Implementation of Space Time Recurrent Memory Network, recurrent network competitive with attentio
Face Mask Detection System built with OpenCV, TensorFlow using Computer Vision concepts
Face mask detection Face Mask Detection System built with OpenCV, TensorFlow using Computer Vision concepts in order to detect face masks in static im
Multiband spectro-radiometric satellite image analysis with K-means cluster algorithm
Multi-band Spectro Radiomertric Image Analysis with K-means Cluster Algorithm Overview Multi-band Spectro Radiomertric images are images comprising of
The Unsupervised Reinforcement Learning Benchmark (URLB)
The Unsupervised Reinforcement Learning Benchmark (URLB) URLB provides a set of leading algorithms for unsupervised reinforcement learning where agent
A project that uses optical flow and machine learning to detect aimhacking in video clips.
waldo-anticheat A project that aims to use optical flow and machine learning to visually detect cheating or hacking in video clips from fps games. Che
Concept Modeling: Topic Modeling on Images and Text
Concept is a technique that leverages CLIP and BERTopic-based techniques to perform Concept Modeling on images.
Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
The official code for the NeurIPS 2021 paper Generalized Jensen-Shannon Divergence Loss for Learning with Noisy Labels
Anomaly Detection Based on Hierarchical Clustering of Mobile Robot Data
We proposed a new approach to detect anomalies of mobile robot data. We investigate each data seperately with two clustering method hierarchical and k-means. There are two sub-method that we used for produce an anomaly score. Then, we merge these two score and produce merged anomaly score as a result.
MultiMix: Sparingly Supervised, Extreme Multitask Learning From Medical Images (ISBI 2021, MELBA 2021)
MultiMix This repository contains the implementation of MultiMix. Our publications for this project are listed below: "MultiMix: Sparingly Supervised,
Code of the paper "Multi-Task Meta-Learning Modification with Stochastic Approximation".
Multi-Task Meta-Learning Modification with Stochastic Approximation This repository contains the code for the paper "Multi-Task Meta-Learning Modifica
Implementation of PersonaGPT Dialog Model
PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz
This is a five-step framework for the development of intrusion detection systems (IDS) using machine learning (ML) considering model realization, and performance evaluation.
AB-TRAP: building invisibility shields to protect network devices The AB-TRAP framework is applicable to the development of Network Intrusion Detectio
Can we visualize a large scientific data set with a surrogate model? We're building a GAN for the Earth's Mantle Convection data set to see if we can!
EarthGAN - Earth Mantle Surrogate Modeling Can a surrogate model of the Earthโs Mantle Convection data set be built such that it can be readily run in
Exponential Graph is Provably Efficient for Decentralized Deep Training
Exponential Graph is Provably Efficient for Decentralized Deep Training This code repository is for the paper Exponential Graph is Provably Efficient
Code Release for the paper "TriBERT: Full-body Human-centric Audio-visual Representation Learning for Visual Sound Separation"
TriBERT This repository contains the code for the NeurIPS 2021 paper titled "TriBERT: Full-body Human-centric Audio-visual Representation Learning for
PyTorch code accompanying the paper "Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning" (NeurIPS 2021).
HIGL This is a PyTorch implementation for our paper: Landmark-Guided Subgoal Generation in Hierarchical Reinforcement Learning (NeurIPS 2021). Our cod
Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning
Audio Domain Adaptation for Acoustic Scene Classification using Disentanglement Learning Reference Abeรer, J. & Mรผller, M. Towards Audio Domain Adapt
Audio Visual Emotion Recognition using TDA
Audio Visual Emotion Recognition using TDA RAVDESS database with two datasets analyzed: Video and Audio dataset: Audio-Dataset: https://www.kaggle.com
Attack on Confidence Estimation algorithm from the paper "Disrupting Deep Uncertainty Estimation Without Harming Accuracy"
Attack on Confidence Estimation (ACE) This repository is the official implementation of "Disrupting Deep Uncertainty Estimation Without Harming Accura
A Closer Look at Reference Learning for Fourier Phase Retrieval
A Closer Look at Reference Learning for Fourier Phase Retrieval This repository contains code for our NeurIPS 2021 Workshop on Deep Learning and Inver
[NeurIPS'21] "AugMax: Adversarial Composition of Random Augmentations for Robust Training" by Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Animashree Anandkumar, and Zhangyang Wang.
AugMax: Adversarial Composition of Random Augmentations for Robust Training Haotao Wang, Chaowei Xiao, Jean Kossaifi, Zhiding Yu, Anima Anandkumar, an
Dynamica causal Bayesian optimisation
Dynamic Causal Bayesian Optimization This is a Python implementation of Dynamic Causal Bayesian Optimization as presented at NeurIPS 2021. Abstract Th
Code accompanying the paper Shared Independent Component Analysis for Multi-subject Neuroimaging
ShICA Code accompanying the paper Shared Independent Component Analysis for Multi-subject Neuroimaging Install Move into the ShICA directory cd ShICA
SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch.
The SpeechBrain Toolkit SpeechBrain is an open-source and all-in-one speech toolkit based on PyTorch. The goal is to create a single, flexible, and us
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective
FL-WBC: Enhancing Robustness against Model Poisoning Attacks in Federated Learning from a Client Perspective Official implementation of "FL-WBC: Enhan
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis
Unified Instance and Knowledge Alignment Pretraining for Aspect-based Sentiment Analysis Requirements python 3.7 pytorch-gpu 1.7 numpy 1.19.4 pytorch_
Code for our paper: Online Variational Filtering and Parameter Learning
Variational Filtering To run phi learning on linear gaussian (Fig1a) python linear_gaussian_phi_learning.py To run phi and theta learning on linear g
[NeurIPS 2021] Source code for the paper "Qu-ANTI-zation: Exploiting Neural Network Quantization for Achieving Adversarial Outcomes"
Qu-ANTI-zation This repository contains the code for reproducing the results of our paper: Qu-ANTI-zation: Exploiting Quantization Artifacts for Achie
Code repository for the paper: Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild (ICCV 2021)
Hierarchical Kinematic Probability Distributions for 3D Human Shape and Pose Estimation from Images in the Wild Akash Sengupta, Ignas Budvytis, Robert
A Snakemake workflow for standardised sc/snRNAseq analysis
single_snake_sequencing - sc/snRNAseq Snakemake Workflow A Snakemake workflow for standardised sc/snRNAseq analysis. Every single cell analysis is sli
This is an official PyTorch implementation of Task-Adaptive Neural Network Search with Meta-Contrastive Learning (NeurIPS 2021, Spotlight).
NeurIPS 2021 (Spotlight): Task-Adaptive Neural Network Search with Meta-Contrastive Learning This is an official PyTorch implementation of Task-Adapti
This repository contains the implementation of the paper: "Towards Frequency-Based Explanation for Robust CNN"
RobustFreqCNN About This repository contains the implementation of the paper "Towards Frequency-Based Explanation for Robust CNN" arxiv. It primarly d
this is a basic python project that I made using python
this is a basic python project that I made using python. This project is only for practice because my python skills are still newbie.
An implementation for the loss function proposed in Decoupled Contrastive Loss paper.
Decoupled-Contrastive-Learning This repository is an implementation for the loss function proposed in Decoupled Contrastive Loss paper. Requirements P
A Higher-Lower web game made in Python using Flask framework.
Higher Lower Web Game Guess the random number from 0 to 9 in this web game made with Python and Flask Framework Modules that were used Random Flask In
Data visualization using matplotlib
Data visualization using matplotlib project instructions Top 5 Most Common Coffee Origins In this visualization I used data from Ankur Chavda on Kaggl
In this project I played with mlflow, streamlit and fastapi to create a training and prediction app on digits
Fastapi + MLflow + streamlit Setup env. I hope I covered all. pip install -r requirements.txt Start app Go in the root dir and run these Streamlit str
Example project demonstrating using Djangoโs test runner with Coverage.py
Example project demonstrating using Djangoโs test runner with Coverage.py Set up with: python -m venv --prompt . venv source venv/bin/activate python
Create and implement a deep learning library from scratch.
In this project, we create and implement a deep learning library from scratch. Table of Contents Deep Leaning Library Table of Contents About The Proj
JAXDL: JAX (Flax) Deep Learning Library
JAXDL: JAX (Flax) Deep Learning Library Simple and clean JAX/Flax deep learning algorithm implementations: Soft-Actor-Critic (arXiv:1812.05905) Transf
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework
(Py)TOD: Tensor-based Outlier Detection, A General GPU-Accelerated Framework Background: Outlier detection (OD) is a key data mining task for identify
A PyTorch Lightning Callback for pushing models to the Hugging Face Hub ๐คโก๏ธ
hf-hub-lightning A callback for pushing lightning models to the Hugging Face Hub. Note: I made this package for myself, mostly...if folks seem to be i
Easy way to build a SaaS application using Python and Dash
EasySaaS This project will be attempt to make a great starting point for your next big business as easy and efficent as possible. This project will cr
PyTorch implementation of "A Simple Baseline for Low-Budget Active Learning".
A Simple Baseline for Low-Budget Active Learning This repository is the implementation of A Simple Baseline for Low-Budget Active Learning. In this pa
An interactive interface for using OpenCV's GrabCut algorithm for image segmentation.
Interactive GrabCut An interactive interface for using OpenCV's GrabCut algorithm for image segmentation. Setup Install dependencies: pip install nump
PyTorch implementation of Memory-based semantic segmentation for off-road unstructured natural environments.
MemSeg: Memory-based semantic segmentation for off-road unstructured natural environments Introduction This repository is a PyTorch implementation of
Demo Python project using Conda and Poetry
Conda Poetry This is a demonstration of how Conda and Poetry can be used in a Python project for dev dependency management and production deployment.
Web-Scraping using Selenium Master
Web-Scraping using Selenium What is the need of Selenium? Some websites don't like to be scrapped and in that case you need to disguise your webscrapi
A lobby boy will create a VPS server when you need one, and destroy it after using it.
Lobbyboy What is a lobby boy? A lobby boy is completely invisible, yet always in sight. A lobby boy remembers what people hate. A lobby boy anticipate
The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL), NeurIPS-2021
Directed Graph Contrastive Learning The PyTorch implementation of Directed Graph Contrastive Learning (DiGCL). In this paper, we present the first con
Create a visualization for Trump's Tweeted Words Using Python
Data Trump's Tweeted Words This plot illustrates twitter word occurences. We already did the coding I needed for this plot, so I was very inspired to
The Empirical Investigation of Representation Learning for Imitation (EIRLI)
The Empirical Investigation of Representation Learning for Imitation (EIRLI)
A lightweight python AUTOmatic-arRAY library.
A lightweight python AUTOmatic-arRAY library. Write numeric code that works for: numpy cupy dask autograd jax mars tensorflow pytorch ... and indeed a
Simple PyTorch hierarchical models.
A python package adding basic hierarchal networks in pytorch for classification tasks. It implements a simple hierarchal network structure based on feed-backward outputs.
A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen.
Master Release Pytorch - Py + Nim A Nim frontend for pytorch, aiming to be mostly auto-generated and internally using ATen. Because Nim compiles to C+
Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression
Quantile Regression DQN Quantile Regression DQN a Minimal Working Example, Distributional Reinforcement Learning with Quantile Regression (https://arx
jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese.
jel: Japanese Entity Linker jel - Japanese Entity Linker - is Bi-encoder based entity linker for japanese. Usage Currently, link and question methods
PyTorch implementation of SmoothGrad: removing noise by adding noise.
SmoothGrad implementation in PyTorch PyTorch implementation of SmoothGrad: removing noise by adding noise. Vanilla Gradients SmoothGrad Guided backpro
Anuvada: Interpretable Models for NLP using PyTorch
Anuvada: Interpretable Models for NLP using PyTorch So, you want to know why your classifier arrived at a particular decision or why your flashy new d
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
PyTorch implementation of Advantage Actor Critic (A2C), Proximal Policy Optimization (PPO), Scalable trust-region method for deep reinforcement learning using Kronecker-factored approximation (ACKTR) and Generative Adversarial Imitation Learning (GAIL).
A method for cleaning and classifying text using transformers.
NLP Translation and Classification The repository contains a method for classifying and cleaning text using NLP transformers. Overview The input data
Simple Machine Learning Tool Kit
Getting started smltk (Simple Machine Learning Tool Kit) package is implemented for helping your work during data preparation testing your model The g
Deep learning image registration library for PyTorch
TorchIR: Pytorch Image Registration TorchIR is a image registration library for deep learning image registration (DLIR). I have integrated several ide
NeurIPS 2021, "Fine Samples for Learning with Noisy Labels"
[Official] FINE Samples for Learning with Noisy Labels This repository is the official implementation of "FINE Samples for Learning with Noisy Labels"
Connection package to a raspberry or any other machine using ssh, it simplifies the deployment scripts and monitoring.
Connection package to a raspberry or any other machine using ssh, it simplifies the deployment scripts and monitoring.
Official Pytorch implementation of "Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021)
Unbiased Classification Through Bias-Contrastive and Bias-Balanced Learning (NeurIPS 2021) Official Pytorch implementation of Unbiased Classification
Deep Learning for Computer Vision final project
Deep Learning for Computer Vision final project
Python IDE or notebook to generate a basic Kepler.gl data visualization
geospatial-data-analysis [readme] Use this code in your Python IDE or notebook to generate a basic Kepler.gl data visualization, without pre-configura
These data visualizations were created for my introductory computer science course using Python
Homework 2: Matplotlib and Data Visualization Overview These data visualizations were created for my introductory computer science course using Python
BloodDonors: Built using Django REST Framework for the API backend and React for the frontend
BloodDonors By Daniel Yuan, Alex Tian, Aaron Pan, Jennifer Yuan As the pandemic raged, one of the side effects was an urgent shortage of blood donatio
Python Program to connect to different VPN servers autoatically using Windscribe VPN.
AutomateVPN What is VPN ? VPN stands for Virtual Private Network , it is a technology that creates a safe and encrypted connectionover a less secure n
Render your templates using .txt files
PizzaX About Run Run tests To run the tests, open your terminal and type python tests.py (WIN) or python3 tests.py (UNX) Using the function To use the
A simple anti-ghostping python bot made using diskord.
Anti Ghostping A simple Anti-Ghostping python bot made with โค using Diskord Requirements No one will use this but, all you need for this bot is: Pytho
A script that trains a model to recognize handwritten digits using the MNIST data set.
handwritten-digits-recognition A script that trains a model to recognize handwritten digits using the MNIST data set. Then it loads external files and
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning.
DirectML is a high-performance, hardware-accelerated DirectX 12 library for machine learning. DirectML provides GPU acceleration for common machine learning tasks across a broad range of supported hardware and drivers, including all DirectX 12-capable GPUs from vendors such as AMD, Intel, NVIDIA, and Qualcomm.
Anti-Backdoor learning (NeurIPS 2021)
Anti-Backdoor Learning PyTorch Code for NeurIPS 2021 paper Anti-Backdoor Learning: Training Clean Models on Poisoned Data. The Anti-Backdoor Learning
Code repository for the work "Multi-Domain Incremental Learning for Semantic Segmentation", accepted at WACV 2022
Multi-Domain Incremental Learning for Semantic Segmentation This is the Pytorch implementation of our work "Multi-Domain Incremental Learning for Sema
Language Models for the legal domain in Spanish done @ BSC-TEMU within the "Plan de las Tecnologรญas del Lenguaje" (Plan-TL).
Spanish legal domain Language Model โ๏ธ This repository contains the page for two main resources for the Spanish legal domain: A RoBERTa model: https:/
This repository contains code and data for "On the Multimodal Person Verification Using Audio-Visual-Thermal Data"
trimodal_person_verification This repository contains the code, and preprocessed dataset featured in "A Study of Multimodal Person Verification Using
This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled Time Series presented at Causal Analysis Workshop 2021.
signed-area-causal-inference This repository contains code demonstrating the methods outlined in Path Signature Area-Based Causal Discovery in Coupled
code for generating data set ES-ImageNet with corresponding training code
es-imagenet-master code for generating data set ES-ImageNet with corresponding training code dataset generator some codes of ODG algorithm The variabl
EgoNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale
EgonNN: Egocentric Neural Network for Point Cloud Based 6DoF Relocalization at the City Scale Paper: EgoNN: Egocentric Neural Network for Point Cloud
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!
CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching
Team Enigma at ArgMining 2021 Shared Task: Leveraging Pretrained Language Models for Key Point Matching This is our attempt of the shared task on Quan
The official repository for "Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds"
Revealing unforeseen diagnostic image features with deep learning by detecting cardiovascular diseases from apical four-chamber ultrasounds The why Im
Implementation of PersonaGPT Dialog Model
PersonaGPT An open-domain conversational agent with many personalities PersonaGPT is an open-domain conversational agent cpable of decoding personaliz
DECAF: Generating Fair Synthetic Data Using Causally-Aware Generative Networks
DECAF (DEbiasing CAusal Fairness) Code Author: Trent Kyono This repository contains the code used for the "DECAF: Generating Fair Synthetic Data Using
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++).
Hierarchical probabilistic 3D U-Net, with attention mechanisms (โ๐๐ต๐ต๐ฆ๐ฏ๐ต๐ช๐ฐ๐ฏ ๐-๐๐ฆ๐ต, ๐๐๐๐ฆ๐ด๐๐ฆ๐ต) and a nested decoder structure with deep supervision (โ๐๐๐ฆ๐ต++). Built in TensorFlow 2.5. Configured for voxel-level clinically significant prostate cancer detection in multi-channel 3D bpMRI scans.
Project repo for the paper SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition
SILT: Self-supervised Lighting Transfer Using Implicit Image Decomposition (BMVC 2021) Project repo for the paper SILT: Self-supervised Lighting Trans
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks
Assessing the Influence of Models on the Performance of Reinforcement Learning Algorithms applied on Continuous Control Tasks This is the master thesi
Instance-Dependent Partial Label Learning
Instance-Dependent Partial Label Learning Installation pip install -r requirements.txt Run the Demo benchmark-random mnist python -u main.py --gpu 0 -
Learning-Augmented Dynamic Power Management
Learning-Augmented Dynamic Power Management This repository contains source code accompanying paper Learning-Augmented Dynamic Power Management with M
Off-policy continuous control in PyTorch, with RDPG, RTD3 & RSAC
arXiv technical report soon available. we are updating the readme to be as comprehensive as possible Please ask any questions in Issues, thanks. Intro
๐ค Transformers: State-of-the-art Natural Language Processing for Pytorch, TensorFlow, and JAX.
English | ็ฎไฝไธญๆ | ็น้ซไธญๆ | ํ๊ตญ์ด State-of-the-art Natural Language Processing for Jax, PyTorch and TensorFlow ๐ค Transformers provides thousands of pretrai
Code for "AutoMTL: A Programming Framework for Automated Multi-Task Learning"
AutoMTL: A Programming Framework for Automated Multi-Task Learning This is the website for our paper "AutoMTL: A Programming Framework for Automated M
Avalanche RL: an End-to-End Library for Continual Reinforcement Learning
Avalanche RL: an End-to-End Library for Continual Reinforcement Learning Avalanche Website | Getting Started | Examples | Tutorial | API Doc | Paper |
Automation application was made by me using Google, Sheet and Slack APIs with Python.
README This application is used to transfer the data in the xlsx document we have to the Google Drive environment and calculate the "total budget" wit
CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary.
CUP-DNN CUP-DNN is a deep neural network model used to predict tissues of origin for cancers of unknown of primary. The model was trained on the expre