JunyiLi23

LLMRec

[WSDM'2024 Oral] "LLMRec: Large Language Models with Graph Augmentation for Recommendation"

AFN-AAAI-20

Source codes for our AAAI'20 paper: Adaptive Factorization Network: Learning Adaptive-Order Feature Interactions

Helen

The official implementation of "Helen: Optimizing CTR Prediction Models with Frequency-wise Hessian Eigenvalue Regularization"

deeplearning_ai_books

deeplearning.ai（吴恩达老师的深度学习课程笔记及资源）

HIEN

Tensorflow implementation for the HIEN

F2R-HMT

UBR4CTR

UBR4CTR is the code for our proposed User Behavior Retrieval for CTR Prediction framework in SIGIR 2020.

deep-ctr-prediction

CTR prediction models based on deep learning(基于深度学习的广告推荐CTR预估模型)

CTR

CTR模型代码和学习笔记总结

DeepCTR

Easy-to-use,Modular and Extendible package of deep-learning based CTR models .

AutoFIS

AutoFIS: Automatic Feature Interaction Selection in Factorization Models for Click-Through Rate Prediction

pytorch-fm

Factorization Machine models in PyTorch

OptFS

This repository contains PyTorch implemenation of WWW 2023 research paper: Optimizing Feature Set for Click-through Rate Prediction.

AIM

AIM: Automatic Interaction Machine for Click-Through Rate Prediction

HIM

FeSAIL

FeSAIL

LargeBatchCTR

Large batch training of CTR models based on DeepCTR with CowClip.

DCIN

AAAI'23 DCIN

DIL

This is an implementation for our SIGIR 2023 paper "Reformulating CTR Prediction: Learning Invariant Feature Interactions for Recommendation" based on PyTorch.

FinalMLP

[AAAI'23] FinalMLP: An Enhanced Two-Stream MLP Model for CTR Prediction https://arxiv.org/abs/2304.00902

EulerNet

This is the official PyTorch implementation for the paper: "EulerNet: Adaptive Feature Interaction Learning via Euler’s Formula for CTR Prediction".

CELS

【PyTorch】Easy-to-use package of Cognitive Evolutionary Search (CELS) for Click-Through Rate Prediction

MAP-CODE

Official Code for paper "MAP: A Model-agnostic Pretraining Framework for Click-through Rate Prediction"