Elamur Research⌕
☰
home / venues / KDD / 2020

KDD 2020 — accepted papers

KDD 2020 is the 2020 edition of the ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD). OpenAlex lists 420 papers of it; our library holds 1 with our summaries. Below: the most cited papers, every accepted paper, and ours with their topics, authors and institutions.

 420papers in the proceedings 1work in our library 601citations of these works

Most cited papers

By their OpenAlex citations; a paper with our summary links to its page here, the others to the original.

  1. Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks ↗Zonghan Wu, Shirui Pan, Guodong Long et al.2,001 citations
  2. USAD ↗Julien Audibert, Pietro Michiardi A, Frédéric Guyard et al.1,065 citations
  3. DeepSpeed ↗Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase et al.815 citations
  4. GCC ↗Jiezhong Qiu, Qibin Chen, Yuxiao Dong et al.777 citations
  5. LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingYiheng Xu, Minghao Li, Lei Cui et al.709 citations · our summary
  6. Graph Structure Learning for Robust Graph Neural Networks ↗Wei Jin, Yao Ma, Xiaorui Liu et al.644 citations
  7. Context-Aware Attentive Knowledge TracingAritra Ghosh, Neil Thomas Heffernan, Andrew Lan580 citations · our summary
  8. Towards Deeper Graph Neural Networks ↗Meng Liu, Hongyang Gao, Shuiwang Ji507 citations
  9. Robust Deep Learning Methods for Anomaly Detection ↗Raghavendra Chalapathy, Nguyen Lu Dang Khoa, Sanjay Chawla502 citations
  10. AM-GCN: Adaptive Multi-channel Graph Convolutional Networks ↗Xiao Wang, Meiqi Zhu, Deyu Bo et al.495 citations

All accepted papers (420)

The most cited first; 1 with our summary link to their page here, the others to the original.

  1. Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks ↗Zonghan Wu, Shirui Pan, Guodong Long et al.2,001 citations
  2. USAD ↗Julien Audibert, Pietro Michiardi A, Frédéric Guyard et al.1,065 citations
  3. DeepSpeed ↗Jeff Rasley, Samyam Rajbhandari, Olatunji Ruwase et al.815 citations
  4. GCC ↗Jiezhong Qiu, Qibin Chen, Yuxiao Dong et al.777 citations
  5. LayoutLM: Pre-training of Text and Layout for Document Image UnderstandingYiheng Xu, Minghao Li, Lei Cui et al.709 citations · our summary
  6. Graph Structure Learning for Robust Graph Neural Networks ↗Wei Jin, Yao Ma, Xiaorui Liu et al.644 citations
  7. Context-Aware Attentive Knowledge TracingAritra Ghosh, Neil Thomas Heffernan, Andrew Lan580 citations · our summary
  8. Towards Deeper Graph Neural Networks ↗Meng Liu, Hongyang Gao, Shuiwang Ji507 citations
  9. Robust Deep Learning Methods for Anomaly Detection ↗Raghavendra Chalapathy, Nguyen Lu Dang Khoa, Sanjay Chawla502 citations
  10. AM-GCN: Adaptive Multi-channel Graph Convolutional Networks ↗Xiao Wang, Meiqi Zhu, Deyu Bo et al.495 citations
  11. On Sampled Metrics for Item Recommendation ↗Walid Krichene, Steffen Rendle495 citations
  12. GPT-GNN ↗Ziniu Hu, Yuxiao Dong, Kuansan Wang et al.446 citations
  13. Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data ↗Chloë Brown, Jagmohan Chauhan, Andreas Grammenos et al.440 citations
  14. Scaling Graph Neural Networks with Approximate PageRank ↗Aleksandar Bojchevski, Johannes Gasteiger, Bryan Perozzi et al.371 citations
  15. Controllable Multi-Interest Framework for Recommendation ↗Yukuo Cen, Jianwei Zhang, Xu Zou et al.338 citations
  16. Improving Conversational Recommender Systems via Knowledge Graph based Semantic Fusion ↗Kun Zhou, Wayne Xin Zhao, Shuqing Bian et al.321 citations
  17. Overview and Importance of Data Quality for Machine Learning Tasks ↗Abhinav Jain, Hima Patel, Lokesh Nagalapatti et al.293 citations
  18. Handling Information Loss of Graph Neural Networks for Session-based Recommendation ↗Tianwen Chen, Raymond Chi-Wing Wong287 citations
  19. Embedding-based Retrieval in Facebook Search ↗Jui-Ting Huang, Ashish Sharma, Shuying Sun et al.276 citations
  20. Towards Physics-informed Deep Learning for Turbulent Flow Prediction ↗Rui Wang, Karthik Kashinath, Mustafa Mustafa et al.273 citations
  21. XGNN: Towards Model-Level Explanations of Graph Neural Networks ↗Hao Yuan, Jiliang Tang, Xia Hu et al.272 citations
  22. Meta-learning on Heterogeneous Information Networks for Cold-start Recommendation ↗Yuanfu Lu, Yuan Fang, Chuan Shi259 citations
  23. Geography-Aware Sequential Location Recommendation ↗Defu Lian, Yongji Wu, Yong Ge et al.253 citations
  24. Adaptive Graph Encoder for Attributed Graph Embedding ↗Ganqu Cui, Jie Zhou, Cheng Yang et al.235 citations
  25. MoFlow: An Invertible Flow Model for Generating Molecular Graphs ↗Chengxi Zang, Fei Wang227 citations

See all 420 papers in KDD 2020 — accepted papers →

 Papers with our summary in our library (1)

The most cited first (OpenAlex citations plus our library's).

  1. Context-Aware Attentive Knowledge TracingACM SIGKDD International Conference on Knowledge Discovery & Data Mining (KDD)Aritra Ghosh, Neil Heffernan, Andrew S. Lan2020 · 601 citations

 Fields

Computer Science (1)

 Top authors

Authors with a page who published here most often: their works here, and the citations of those works.

🧑‍🔬Andrew Lan1 work here · 601 citations

 Top institutions

Institutions on the bylines of its works here, by the number of works.

🎓Worcester Polytechnic InstituteWorcester · United States1 work here🎓University of Massachusetts AmherstAmherst Center · United States1 work here

works and citations from OpenAlex and our library.

↑ back to top

This page in Markdown → https://md.research.elamur.ai/free/en/venues/acm-sigkdd-international-conference-on-knowledge-discovery-data-mining-kdd/2020/