evison Goto Github PK

act-plus-plus

Imitation Learning algorithms with Co-traing for Mobile ALOHA: ACT, Diffusion Policy, VINN

aios

AIOS: LLM Agent Operating System

autolossgen

AutoLossGen: Automatic Loss Function Generation for Recommender Systems

awesome-transformers

A curated list of awesome transformer models.

cafe

Cafe: Coarse-to-Fine Neural Symbolic Reasoning for Explainable Recommendation

ccf

Causal Collaborative Filtering

chicker

Chicker: An Open-source Location-based Personalized Restaurant Recommender System based on HTML5

clip-adapter

connect4

A General Open-source Framework for Experimenting Novel AI algorithms based on the Connect Four Game

conversational

Code for paper: Towards Conversational Search and Recommendation: System Ask, User Respond

conversearch

cookie

A Dataset for Conversational Recommendation over KnowledgeGraph in E-commerce

counter

Counterfactual Explainable Recommendation

csrankings

A web app for ranking computer science departments according to their research output in selective venues, and for finding active faculty across a wide range of areas.

dccf

Deconfounded Causal Collaborative Filtering

der

Code for "Dynamic Explainable Recommendation based on Neural Attentive Models"

distcrawler

A Distributed Web Crawler based on Hadoop and HBase

double-blind-reviewing.github.io

dowhy

DoWhy is a Python library that makes it easy to estimate causal effects. DoWhy is based on a unified language for causal inference, combining causal graphical models and potential outcomes frameworks.

drr

code for the paper "Personalized Re-ranking for E-commerce Recommender Systems"

dyccf

Dynamic Causal Collaborative Filtering

ears2018workshop

echochamberinecommerce

er-mpum

Code for paper: Multi-Product Utility Maximization for Economic Recommendation

er-surplus

Code for paper: Economic Recommendation with Surplus Maximization

evison.github.io

explainable-product-search-with-a-dynamic-relation-embedding-model

explainable-recommendation

explainablefold

extra

SIGIR'21, EXTRA: Explanation Ranking Datasets for Explainable Recommendation