Pinned Repositories
AI-Feynman
awesome-papers
Papers & presentations from Hugging Face's weekly science day
batterybert
BatteryBERT: A Pre-trained Language Model for Battery Database Enhancement
bert-loves-chemistry
bert-loves-chemistry: a repository of HuggingFace models applied on chemical SMILES data for drug design, chemical modelling, etc.
BERT-Relation-Extraction
PyTorch implementation for "Matching the Blanks: Distributional Similarity for Relation Learning" paper
Borges
Web Scarping Engines
Candidate_Skill_Assessment_using_Graph_Neural_Network
Final Year Project work
Categorizing-figures-from-biomedical-research-articles-using-deep-neural-networks-and-Bioassays
The project’s main objective is to extract knowledge from the biomedical research papers that contain diagrams/charts, i.e., bar graphs, line graph, boxplot, images of CT scans, cells, and other types of biological tests (known as assays). Research papers contain panels that have information in images or diagrams. The goal is to identify each panel from given datasets and categorize it into BioAssay Ontology categories with the help of machine learning and deep neural networks model. An additional focus of the project is to predict and identify the similarities between BioAssay Ontology categories and find their correlation. The dataset we are using is from SourceData, an initiative by EMBO (European Molecular Biology Organization). So, this project will record details of the correlation of BioAssay Ontology categories, predict and identify the panel with the help of a Convolutional neural network model.
Graph_Convolutional_Networks_Node_Classification
python-one-liners
This repository contains python one-liners obtained from various sources.
vinven7's Repositories
vinven7/Graph_Convolutional_Networks_Node_Classification
vinven7/python-one-liners
This repository contains python one-liners obtained from various sources.
vinven7/batterybert
BatteryBERT: A Pre-trained Language Model for Battery Database Enhancement
vinven7/Categorizing-figures-from-biomedical-research-articles-using-deep-neural-networks-and-Bioassays
The project’s main objective is to extract knowledge from the biomedical research papers that contain diagrams/charts, i.e., bar graphs, line graph, boxplot, images of CT scans, cells, and other types of biological tests (known as assays). Research papers contain panels that have information in images or diagrams. The goal is to identify each panel from given datasets and categorize it into BioAssay Ontology categories with the help of machine learning and deep neural networks model. An additional focus of the project is to predict and identify the similarities between BioAssay Ontology categories and find their correlation. The dataset we are using is from SourceData, an initiative by EMBO (European Molecular Biology Organization). So, this project will record details of the correlation of BioAssay Ontology categories, predict and identify the panel with the help of a Convolutional neural network model.
vinven7/CS224W-Colab
Solutions for CS224W Winter 2021 Colab
vinven7/DeepLearningExamples
Deep Learning Examples
vinven7/FDGNN-Fraud-Address-Detection-on-Ethereum-using-Graph-Neural-Network
vinven7/generative-ai-for-beginners
12 Lessons, Get Started Building with Generative AI 🔗 https://microsoft.github.io/generative-ai-for-beginners/
vinven7/GFPGAN
GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.
vinven7/GNNs-for-NLP
Tutorial: Graph Neural Networks for Natural Language Processing at EMNLP 2019 and CODS-COMAD 2020
vinven7/graph-ml-notebooks
vinven7/Graph-Neural-Networks-1
This is a collection of all my learning material and implementations of Graph Neural Nets
vinven7/Graph-Neural-Networks-Collection
Collection of graph neural networks repositories from all over
vinven7/Graph-Neural-Networks-for-Music-Genre-Recognition
vinven7/graph4nlp_demo
This repo is to present various code demos on how to use our Graph4NLP library.
vinven7/hyperDB
A hyper-fast local vector database for use with LLM Agents. Now accepting SAFEs at $135M cap.
vinven7/LLaVA
[NeurIPS'23 Oral] Visual Instruction Tuning (LLaVA) built towards GPT-4V level capabilities and beyond.
vinven7/Movie-Recommender-System-Using-Graph-Neural-Networks
vinven7/perovskitedatabase
vinven7/Predicting-Drug-Interactions-using-Graph-Neural-Networks-DGL-
vinven7/PythonDataScienceHandbook
Python Data Science Handbook: full text in Jupyter Notebooks
vinven7/Pytorch-tutorial
vinven7/Qugel
This work presents Qugel , a QML platform which utilizes shallow quantum neural network (QNN) image encoders composed of parametrized quantum circuits (PQCs) for solving categorial image classification challenges.
vinven7/rev
Reverse-Engineering Visualizations (REV).
vinven7/sgg
Train Scene Graph Generation for Visual Genome and GQA in PyTorch >= 1.2 with improved zero and few-shot generalization.
vinven7/simplegmail
A simple Gmail API client for applications in Python
vinven7/Solubility-Prediction-with-Graph-Neural-Networks
GNN, GCN, Molecular Solubility, RDKit, Cheminformatics
vinven7/spaCy
💫 Industrial-strength Natural Language Processing (NLP) in Python
vinven7/vision
Datasets, Transforms and Models specific to Computer Vision
vinven7/wordlebot
solver for the game Wordle