mengxiaozhibo

AlgoNotes

【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.

Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

Awesome-Pretraining-for-Graph-Neural-Networks

A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).

Awesome-RSPapers

Recommender System Papers

CARP

The implementation of “A Capsule Network for Recommendation and Explaining What You Like and Dislike”, Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu, https://dl.acm.org/citation.cfm?doid=3331184.3331216

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)

DEI2N

DMIN

GEIN

mengxiaozhibo/DMIN

mengxiaozhibo/DEI2N

mengxiaozhibo/GEIN

mengxiaozhibo/AlgoNotes

【浅梦学习笔记】文章汇总:包含 排序&CXR预估，召回匹配，用户画像&特征工程，推荐搜索综合 计算广告，大数据，图算法，NLP&CV，求职面试 等内容

mengxiaozhibo/Awesome-Deep-Learning-Papers-for-Search-Recommendation-Advertising

Awesome Deep Learning papers for industrial Search, Recommendation and Advertising. They focus on Embedding, Matching, Ranking (CTR and CVR prediction), Post Ranking, Multi-task Learning, Graph Neural Networks, Transfer Learning, Reinforcement Learning, Self-supervised Learning and so on.

mengxiaozhibo/Awesome-LLM

Awesome-LLM: a curated list of Large Language Model

mengxiaozhibo/Awesome-Pretraining-for-Graph-Neural-Networks

A curated list of papers on pre-training for graph neural networks (Pre-train4GNN).

mengxiaozhibo/Awesome-RSPapers

Recommender System Papers

mengxiaozhibo/CARP

The implementation of “A Capsule Network for Recommendation and Explaining What You Like and Dislike”, Chenliang Li, Cong Quan, Li Peng, Yunwei Qi, Yuming Deng, Libing Wu, https://dl.acm.org/citation.cfm?doid=3331184.3331216

mengxiaozhibo/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)

mengxiaozhibo/deep-multi-representational-item-network

mengxiaozhibo/DeepCTR

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

mengxiaozhibo/DeepInterestNetwork

mengxiaozhibo/DeepMatch

A deep matching model library for recommendations & advertising. It's easy to train models and to export representation vectors for user and item which can be used for ANN search.

mengxiaozhibo/DIEN-pipline

DIEN-pipline implement

mengxiaozhibo/DSIN

Code for the IJCAI'19 paper "Deep Session Interest Network for Click-Through Rate Prediction"

mengxiaozhibo/DuoRec

Code for WSDM 2022 paper, Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.

mengxiaozhibo/ecg

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

mengxiaozhibo/ItemEvolutionNet

mengxiaozhibo/luoxi_models

see readme

mengxiaozhibo/MIAN-CTR

Dataset and code for “Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction”

mengxiaozhibo/models

mengxiaozhibo/R3S

Real-time Relevant Recommendation Suggestion

mengxiaozhibo/Reco-papers

Classic papers and resources on recommendation

mengxiaozhibo/RecommenderSystems

mengxiaozhibo/tensorflow_practice

tensorflow实战练习，包括强化学习、推荐系统、nlp等

mengxiaozhibo/tgin

mengxiaozhibo/the-algorithm

Source code for Twitter's Recommendation Algorithm

mengxiaozhibo/transformer

A TensorFlow Implementation of the Transformer: Attention Is All You Need

mengxiaozhibo/WWW-22-DIHN