{"payload":{"pageCount":2,"repositories":[{"type":"Public","name":"tgm-dlm","owner":"CRIPAC-DIG","isFork":false,"description":"Code for AAAI24 paper Text-Guided Molecule Generation with Diffusion Language Model ","topicNames":["language-model","diffusion-models","molecule-generation","text-guided-generation"],"topicsNotShown":0,"allTopics":["language-model","diffusion-models","molecule-generation","text-guided-generation"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":13,"forksCount":5,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-20T09:01:45.534Z"}},{"type":"Public","name":"shuwu.github.io","owner":"CRIPAC-DIG","isFork":true,"description":"","topicNames":[],"topicsNotShown":0,"allTopics":[],"primaryLanguage":{"name":"HTML","color":"#e34c26"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-05-16T06:51:08.056Z"}},{"type":"Public","name":"LGCF","owner":"CRIPAC-DIG","isFork":false,"description":"[CIKM 2021] The source code of \"Fully Hyperbolic Graph Convolution Network for Recommendation\"","topicNames":["graph-neural-networks","label-encoder"],"topicsNotShown":0,"allTopics":["graph-neural-networks","label-encoder"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":0,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-26T09:47:02.389Z"}},{"type":"Public","name":"hetgsl","owner":"CRIPAC-DIG","isFork":false,"description":"[CIKM 2021] Code and dataset for \"Label-informed Graph Structure Learning for Node Classification\"","topicNames":["label-encoding","graph-neural-networks"],"topicsNotShown":0,"allTopics":["label-encoding","graph-neural-networks"],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-26T09:35:03.537Z"}},{"type":"Public","name":"SCGAN","owner":"CRIPAC-DIG","isFork":false,"description":"[ICME 2019] Source code and datasets for \"Semi-supervised Compatibility Learning Across Categories for Clothing Matching\"","topicNames":["semi-supervised-learning","unsupervised-learning","adversarial-learning","fashion-recommendation"],"topicsNotShown":0,"allTopics":["semi-supervised-learning","unsupervised-learning","adversarial-learning","fashion-recommendation"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":8,"forksCount":3,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-26T09:10:01.261Z"}},{"type":"Public","name":"GRACE","owner":"CRIPAC-DIG","isFork":false,"description":"[GRL+ @ ICML 2020] PyTorch implementation for \"Deep Graph Contrastive Representation Learning\" (https://arxiv.org/abs/2006.04131v2)","topicNames":["machine-learning","deep-learning","graph-representation-learning","contrastive-learning"],"topicsNotShown":0,"allTopics":["machine-learning","deep-learning","graph-representation-learning","contrastive-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":7,"starsCount":290,"forksCount":55,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T08:21:20.120Z"}},{"type":"Public","name":"H-GCN","owner":"CRIPAC-DIG","isFork":false,"description":"[IJCAI 2019] Source code and datasets for \"Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification\"","topicNames":["machine-learning","semi-supervised-learning","hierarchical-models","graph-convolutional-networks","node-classification","graph-neural-networks","network-mining"],"topicsNotShown":0,"allTopics":["machine-learning","semi-supervised-learning","hierarchical-models","graph-convolutional-networks","node-classification","graph-neural-networks","network-mining"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":114,"forksCount":25,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T08:14:55.014Z"}},{"type":"Public","name":"HCA","owner":"CRIPAC-DIG","isFork":true,"description":"[Neurocomputing 2019] Code for \"A Hierarchical Contextual Attention-based Network for Sequential Recommendation\"","topicNames":["recurrent-neural-networks","attention-mechanism","short-term","location-prediction","sequential-recommendation","next-basket-recommendation"],"topicsNotShown":0,"allTopics":["recurrent-neural-networks","attention-mechanism","short-term","location-prediction","sequential-recommendation","next-basket-recommendation"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":3,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T08:05:59.448Z"}},{"type":"Public","name":"MV-RNN","owner":"CRIPAC-DIG","isFork":true,"description":"[TKDE 2018] Code for \"MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation\"","topicNames":["recurrent-neural-networks","multi-view-learning","sequential-recommendation","cold-start-problem"],"topicsNotShown":0,"allTopics":["recurrent-neural-networks","multi-view-learning","sequential-recommendation","cold-start-problem"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":2,"forksCount":6,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T08:02:50.535Z"}},{"type":"Public","name":"TAGNN","owner":"CRIPAC-DIG","isFork":false,"description":"[SIGIR 2020] Python implementation for \"TAGNN: Target Attentive Graph Neural Networks for Session-based Recommendation\"","topicNames":["machine-learning","recommender-systems","graph-neural-networks","session-based-recommendation","target-aware-attention"],"topicsNotShown":0,"allTopics":["machine-learning","recommender-systems","graph-neural-networks","session-based-recommendation","target-aware-attention"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":2,"starsCount":52,"forksCount":14,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T07:59:00.808Z"}},{"type":"Public","name":"TextING","owner":"CRIPAC-DIG","isFork":false,"description":"[ACL 2020] Tensorflow implementation for \"Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks\"","topicNames":["natural-language-processing","text-classification","inductive-learning","graph-neural-networks"],"topicsNotShown":0,"allTopics":["natural-language-processing","text-classification","inductive-learning","graph-neural-networks"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":15,"starsCount":175,"forksCount":57,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T07:56:25.680Z"}},{"type":"Public","name":"GRMM","owner":"CRIPAC-DIG","isFork":false,"description":"[AAAI 2021] PyTorch implementation for \"A Graph-based Relevance Matching Model for Ad-hoc Retrieval\"","topicNames":["retrieve","document-level","graph-neural-networks","term-level-matching"],"topicsNotShown":0,"allTopics":["retrieve","document-level","graph-neural-networks","term-level-matching"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":6,"forksCount":2,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T07:49:42.856Z"}},{"type":"Public","name":"GCA","owner":"CRIPAC-DIG","isFork":false,"description":"[WWW 2021] Source code for \"Graph Contrastive Learning with Adaptive Augmentation\"","topicNames":["deep-learning","pytorch","self-supervised-learning","graph-representation-learning","contrastive-learning","graph-contrastive-learning"],"topicsNotShown":0,"allTopics":["deep-learning","pytorch","self-supervised-learning","graph-representation-learning","contrastive-learning","graph-contrastive-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":7,"starsCount":154,"forksCount":26,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T07:48:27.194Z"}},{"type":"Public","name":"DyGCN","owner":"CRIPAC-DIG","isFork":false,"description":"Code for \"DyGCN: Dynamic Graph Embedding with Graph Convolutional Network\"","topicNames":["graph-convolutional-networks","dynamic-graph-embedding"],"topicsNotShown":0,"allTopics":["graph-convolutional-networks","dynamic-graph-embedding"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":2,"starsCount":31,"forksCount":4,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T07:39:26.955Z"}},{"type":"Public","name":"Distance2Pre","owner":"CRIPAC-DIG","isFork":true,"description":"[PAKDD 2019] Code for \"Distance2Pre: Personalized Spatial Preference for Next Point-of-Interest Prediction\"","topicNames":["deep-learning","point-of-interest"],"topicsNotShown":0,"allTopics":["deep-learning","point-of-interest"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":7,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-25T07:32:55.938Z"}},{"type":"Public","name":"A-PGNN","owner":"CRIPAC-DIG","isFork":false,"description":"[TKDE 2021] Source code and datasets for the paper \"Personalizing Graph Neural Networks with Attention Mechanism for Session-based Recommendation\" ","topicNames":["tensorflow","attention-mechanism","graph-neural-networks","session-aware-recommendation"],"topicsNotShown":0,"allTopics":["tensorflow","attention-mechanism","graph-neural-networks","session-aware-recommendation"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":5,"starsCount":80,"forksCount":13,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:44:04.507Z"}},{"type":"Public","name":"NGNN","owner":"CRIPAC-DIG","isFork":false,"description":"[WWW 2019] Code and dataset for \"Dressing as a Whole: Outfit Compatibility Learning Based on Node-wise Graph Neural Networks\"","topicNames":["attention-mechanism","graph-neural-networks","fashion-recommendation","multiple-modalities","node-represents"],"topicsNotShown":0,"allTopics":["attention-mechanism","graph-neural-networks","fashion-recommendation","multiple-modalities","node-represents"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":12,"starsCount":80,"forksCount":23,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:29:57.262Z"}},{"type":"Public","name":"DGCF","owner":"CRIPAC-DIG","isFork":false,"description":"[ICDM 2020] Python implementation for \"Dynamic Graph Collaborative Filtering.\"","topicNames":["collaborative-filtering","recommender-system","dynamic-graphs"],"topicsNotShown":0,"allTopics":["collaborative-filtering","recommender-system","dynamic-graphs"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":40,"forksCount":6,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:16:23.735Z"}},{"type":"Public","name":"GHRM","owner":"CRIPAC-DIG","isFork":false,"description":"[WWW 2021] Source code and datasets for the paper \"Graph-based Hierarchical Relevance Matching Signals for Ad-hoc Retrieval\".","topicNames":["deep-learning","graph-neural-networks","hierarchical-model","ad-hoc-retrieval"],"topicsNotShown":0,"allTopics":["deep-learning","graph-neural-networks","hierarchical-model","ad-hoc-retrieval"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":3,"starsCount":9,"forksCount":7,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:12:11.415Z"}},{"type":"Public","name":"DESTINE","owner":"CRIPAC-DIG","isFork":false,"description":"[CIKM 2021] Implementations for Disentangled Self-Attentive Neural Networks for Click-Through Rate Prediction","topicNames":["ctr-prediction","disentangled","feature-interactions","self-attentive-neural-networks"],"topicsNotShown":0,"allTopics":["ctr-prediction","disentangled","feature-interactions","self-attentive-neural-networks"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":7,"forksCount":2,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:08:20.100Z"}},{"type":"Public","name":"Fi_GNN","owner":"CRIPAC-DIG","isFork":false,"description":"[CIKM 2019] Code and dataset for \"Fi-GNN: Modeling Feature Interactions via Graph Neural Networks for CTR Prediction\"","topicNames":["ctr-prediction","graph-neural-networks"],"topicsNotShown":0,"allTopics":["ctr-prediction","graph-neural-networks"],"primaryLanguage":null,"pullRequestCount":0,"issueCount":6,"starsCount":81,"forksCount":28,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:04:23.427Z"}},{"type":"Public","name":"LATTICE","owner":"CRIPAC-DIG","isFork":false,"description":"[ACMMM 2021] PyTorch implementation for \"Mining Latent Structures for Multimedia Recommendation\"","topicNames":["deep-learning","pytorch","recommender-systems","personalized-recommendation","graph-structure-learning","multimedia-recommendation"],"topicsNotShown":0,"allTopics":["deep-learning","pytorch","recommender-systems","personalized-recommendation","graph-structure-learning","multimedia-recommendation"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":35,"forksCount":8,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-24T09:00:06.226Z"}},{"type":"Public","name":"MICRO","owner":"CRIPAC-DIG","isFork":false,"description":"","topicNames":["collaborative-filtering","graph-convolutions","contrastive-learning","multimedia-recommendation","multiple-modalities"],"topicsNotShown":0,"allTopics":["collaborative-filtering","graph-convolutions","contrastive-learning","multimedia-recommendation","multiple-modalities"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":22,"forksCount":5,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T09:04:20.459Z"}},{"type":"Public","name":"GETRAL","owner":"CRIPAC-DIG","isFork":false,"description":"The source code of \"Adversarial Contrastive Learning for Evidence-aware Fake News Detection with Graph Neural Networks","topicNames":["adversarial-learning","evidence-based","fake-news-detection","graph-contrastive-learning","semantic-learning"],"topicsNotShown":0,"allTopics":["adversarial-learning","evidence-based","fake-news-detection","graph-contrastive-learning","semantic-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":1,"starsCount":15,"forksCount":2,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T08:37:45.798Z"}},{"type":"Public","name":"CF-FEND","owner":"CRIPAC-DIG","isFork":false,"description":"[SIGIR 2022] Source code and datasets for \"Bias Mitigation for Evidence-aware Fake News Detection by Causal Intervention\".","topicNames":["causal-inference","evidence-based","debiasing","fake-news-detection","causal-intervention"],"topicsNotShown":0,"allTopics":["causal-inference","evidence-based","debiasing","fake-news-detection","causal-intervention"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":7,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T08:36:58.532Z"}},{"type":"Public","name":"RHGN","owner":"CRIPAC-DIG","isFork":false,"description":"Source code for CIKM 2021 paper for Relation-aware Heterogeneous Graph for User Profiling","topicNames":["user-profiling","graph-neural-networks","transformer-architecture","heterogeneous-graph-neural-network","meta-relational-learning"],"topicsNotShown":0,"allTopics":["user-profiling","graph-neural-networks","transformer-architecture","heterogeneous-graph-neural-network","meta-relational-learning"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":7,"forksCount":1,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T08:36:13.271Z"}},{"type":"Public","name":"GET","owner":"CRIPAC-DIG","isFork":false,"description":"[WWW 2022] The source code of \"Evidence-aware Fake News Detection with Graph Neural Networks\"","topicNames":["fake-news-detection","graph-structure-learning","semantic-learning","evidence-based-fake-news-detection"],"topicsNotShown":0,"allTopics":["fake-news-detection","graph-structure-learning","semantic-learning","evidence-based-fake-news-detection"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":1,"issueCount":6,"starsCount":40,"forksCount":9,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T08:35:49.057Z"}},{"type":"Public","name":"DGSR","owner":"CRIPAC-DIG","isFork":false,"description":"[TKDE 2022] The source code of \"Dynamic Graph Neural Networks for Sequential Recommendation\"","topicNames":["recommender-system","graph-neural-networks","sequential-recommendation","dynamic-graph-embedding"],"topicsNotShown":0,"allTopics":["recommender-system","graph-neural-networks","sequential-recommendation","dynamic-graph-embedding"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":6,"starsCount":56,"forksCount":12,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T08:19:58.723Z"}},{"type":"Public","name":"GraphCTR","owner":"CRIPAC-DIG","isFork":false,"description":"This repo includes some graph-based CTR prediction models and other representative baselines.","topicNames":["factorization-machines","graph-neural-networks","graph-factorization","feature-interactions"],"topicsNotShown":0,"allTopics":["factorization-machines","graph-neural-networks","graph-factorization","feature-interactions"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":4,"starsCount":61,"forksCount":13,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T08:14:51.605Z"}},{"type":"Public","name":"HGLS","owner":"CRIPAC-DIG","isFork":false,"description":"[WWW 2023] The source code of \"Learning Long- and Short-term Representations for Temporal Knowledge Graph Reasoning\"","topicNames":["hierarchical-models","temporal-knowledge-graph"],"topicsNotShown":0,"allTopics":["hierarchical-models","temporal-knowledge-graph"],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":3,"starsCount":23,"forksCount":5,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2024-04-23T07:54:43.325Z"}}],"repositoryCount":35,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"Repositories"}