dmis-lab / KitchenScale

KitchenScale: Learning Food Numeracy from Recipes through Context-Aware Ingredient Quantity Prediction

hugochan / PFoodReq

Code & data accompanying the WSDM 2021 paper "Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph"

lamypark / Reciptor

Code & data for the KDD 2020 paper "Reciptor: An Effective Pretrained Model for Recipe Representation Learning"

foodkg / foodkg.github.io

benedekrozemberczki / Splitter

A Pytorch implementation of "Splitter: Learning Node Representations that Capture Multiple Social Contexts" (WWW 2019).

majumderb / recipe-personalization

EMNLP 2019: Generating Personalized Recipes from Historical User Preferences

dmis-lab / KitcheNette

KitcheNette: Predicting and Recommending Food Ingredient Pairings using Siamese Neural Networks

dmis-lab / biobert

Bioinformatics'2020: BioBERT: a pre-trained biomedical language representation model for biomedical text mining

frenetic-be / MLFoodPairing

Food pairing using Machine Learning

prakashpandey9 / Text-Classification-Pytorch

Text classification using deep learning models in Pytorch