Barcavin
Actually the success of all Machine Learning algorithms depends on how you present the data
University of Notre DameNotre Dame, IN
Pinned Repositories
ai-deadlines
:alarm_clock: AI conference deadline countdowns
Barcavin.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
beautiful-jekyll-archive
✨ Build a beautiful and simple website in literally minutes. Demo at https://beautifuljekyll.com
dash_python
deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
document_embedding
Implementation of the document embedding method.
efficient-node-labelling
Code for Neurips 2024 paper: "Pure Message Passing Can Estimate Common Neighbor for Link Prediction"
FakeEdge
nlp_model
NN_built_from_scratch
The implementation of back-propagation algorithm from scratch
Barcavin's Repositories
Barcavin/efficient-node-labelling
Code for Neurips 2024 paper: "Pure Message Passing Can Estimate Common Neighbor for Link Prediction"
Barcavin/document_embedding
Implementation of the document embedding method.
Barcavin/FakeEdge
Barcavin/nlp_model
Barcavin/ai-deadlines
:alarm_clock: AI conference deadline countdowns
Barcavin/Barcavin.github.io
Github Pages template for academic personal websites, forked from mmistakes/minimal-mistakes
Barcavin/beautiful-jekyll-archive
✨ Build a beautiful and simple website in literally minutes. Demo at https://beautifuljekyll.com
Barcavin/dash_python
Barcavin/deep-learning-v2-pytorch
Projects and exercises for the latest Deep Learning ND program https://www.udacity.com/course/deep-learning-nanodegree--nd101
Barcavin/eda_nlp
Data augmentation for NLP, presented at EMNLP 2019
Barcavin/income_analysis
Barcavin/LongitudinalClustering
Barcavin/NN_built_from_scratch
The implementation of back-propagation algorithm from scratch
Barcavin/loss-landscape
Code for visualizing the loss landscape of neural nets
Barcavin/nanoGPT
The simplest, fastest repository for training/finetuning medium-sized GPTs.
Barcavin/ogb
Benchmark datasets, data loaders, and evaluators for graph machine learning
Barcavin/pytorch_geometric
Graph Neural Network Library for PyTorch
Barcavin/shap
A unified approach to explain the output of any machine learning model.
Barcavin/subgraph-sketching
code for Graph Neural Networks for Link Prediction with Subgraph Sketching https://arxiv.org/abs/2209.15486
Barcavin/transformers
🤗Transformers: State-of-the-art Natural Language Processing for Pytorch and TensorFlow 2.0.