Xiaoli Li

Artificial Intelligence · International Joint Conference on Artificial Intelligence · 2002–2021

A researcher in the Science corpus: 15 papers; trusts 205 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 99 citations into it; #11,640 of 35,345 by trust here, #9,170 by citations
• Molecular Biology — 92 citations into it; #16,717 of 17,773 by trust here, #11,608 by citations
• Computer Vision and Pattern Recognition — 48 citations into it; #10,065 of 21,575 by trust here, #11,498 by citations
• Information Systems — 44 citations into it; #4,847 of 8,771 by trust here, #4,012 by citations
• Computational Theory and Mathematics — 36 citations into it; #11,838 of 12,182 by trust here, #4,696 by citations
• Natural Language Processing — 35 citations into it
• Model Architectures — 28 citations into it
• Signal Processing — 19 citations into it

Whom Xiaoli Li trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Yann LeCun
2. Yoshua Bengio
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Diederik P. Kingma
6. Gary D. Bader
7. Ilya Sutskever
8. Ruslan Salakhutdinov
9. Kaiming He
10. Andrew McCallum

Who trusts Xiaoli Li overall

1. Shehroz S. Khan
2. Jessa Bekker
3. Adrien Barbaresi
4. B. Liu
5. Min Wu
6. Xiang Li
7. Rui Zhao
8. Fantine Mordelet

Papers from Xiaoli Li's perspective

Ordered by how strongly the researchers Xiaoli Li trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Drug-target interaction prediction by learning from local information and neighbors (2013) — 347 citations
• Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction (2016) — 354 citations
• Computational approaches for detecting protein complexes from protein interaction networks: a survey (2010) — 345 citations
• A core-attachment based method to detect protein complexes in PPI networks (2009) — 351 citations
• An Attention-Based Deep Learning Approach for Sleep Stage Classification With Single-Channel EEG (2021) — 535 citations
• Time-Series Representation Learning via Temporal and Contextual Contrasting (2021) — 834 citations
• Machine Remaining Useful Life Prediction via an Attention-Based Deep Learning Approach (2021) — 521 citations
• Global Context Enhanced Graph Neural Networks for Session-based Recommendation (2020) — 626 citations
• Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification (2019) — 363 citations
• Deep Convolutional Neural Network Based Regression Approach for Estimation of Remaining Useful Life (2016) — 868 citations
• Deep Convolutional Neural Networks on Multichannel Time Series for Human Activity Recognition (2015) — 1,181 citations
• Rank-GeoFM: A Ranking based Geographical Factorization Method for Point of Interest Recommendation (2015) — 359 citations
• Eliminating noisy information in Web pages for data mining (2003) — 305 citations
• Building text classifiers using positive and unlabeled examples (2003) — 793 citations
• Partially Supervised Classification of Text Documents (2002) — 660 citations