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We present a generic and trend-aware curriculum learning approach for graph neural networks.
A statistical interpretation of term specificity and its application in retrieval
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Probabilistic models of information retrieval based on measuring the divergence from randomness
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Curriculum learning
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Churchill’s Pocketbook of Differential Diagnosis E-Book
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Cícero dos Santos, Bing Xiang, and Bowen Zhou. 2015 · 2015
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Self-paced curriculum learning
Lu Jiang, Deyu Meng, Qian Zhao, Shiguang Shan, and Alexander G Hauptmann. 2015 · 2015
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Adam: A method for stochastic optimization
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Distant supervision for relation extraction via piecewise convolutional neural networks
Daojian Zeng, Kang Liu, Yubo Chen, and Jun Zhao. 2015 · 2015
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Inferring implicit causal relationships in biomedical literature
Halil Kilicoglu. 2016 · 2016
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Neural relation extraction with selective attention over instances
Yankai Lin, Shiqi Shen, Zhiyuan Liu, Huanbo Luan, and Maosong Sun. 2016 · 2016
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Repeat before forgetting: Spaced repetition for efficient and effective training of neural networks
Hadi Amiri, Timothy Miller, and Guergana Savova. 2017 · 2017
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Graph convolutional encoders for syntax-aware neural machine translation
Jasmijn Bastings, Ivan Titov, Wilker Aziz, Diego Marcheggiani, and Khalil Sima’an. 2017 · 2017
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Protein interface prediction using graph convolutional networks
Alex Fout, Jonathon Byrd, Basir Shariat, and Asa Ben-Hur. 2017 · 2017
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Inductive representation learning on large graphs
Will Hamilton, Zhitao Ying, and Jure Leskovec. 2017 · 2017
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Thomas N Kipf and Max Welling. 2017 · 2017
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Encoding sentences with graph convolutional networks for semantic role labeling
Omim. org: leveraging knowledge across phenotype–gene relationships
Joanna S Amberger, Carol A Bocchini, Alan F Scott, and Ada Hamosh. 2019 · 2019
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Distantly supervised biomedical knowledge acquisition via knowledge graph based attention
Qin Dai, Naoya Inoue, Paul Reisert, Ryo Takahashi, and Kentaro Inui. 2019 · 2019
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Data parameters: A new family of parameters for learning a differentiable curriculum
Shreyas Saxena, Oncel Tuzel, and Dennis DeCoste. 2019 · 2019
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A silver standard corpus of human phenotype-gene relations
Diana Sousa, André Lamúrias, and Francisco M Couto. 2019 · 2019
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Subgraph neural networks
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Diego Marcheggiani and Ivan Titov. 2017 · 2017
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Cross-sentence n-ary relation extraction with graph lstms
Nanyun Peng, Hoifung Poon, Chris Quirk, Kristina Toutanova, and Wen-tau Yih. 2017 · 2017
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Distant supervision for relation extraction beyond the sentence boundary
Chris Quirk and Hoifung Poon. 2017 · 2017
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Mentornet: Learning data-driven curriculum for very deep neural networks on corrupted labels
Lu Jiang, Zhengyuan Zhou, Thomas Leung, Li-Jia Li, and Li Fei-Fei. 2018 · 2018
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Exploiting semantics in neural machine translation with graph convolutional networks
Diego Marcheggiani, Jasmijn Bastings, and Ivan Titov. 2018 · 2018
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Large-scale hierarchical text classification with recursively regularized deep graph-cnn
Hao Peng, Jianxin Li, Yu He, Yaopeng Liu, Mengjiao Bao, Lihong Wang, Yangqiu Song, and Qiang Yang. 2018 · 2018
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A graph-to-sequence model for amr-to-text generation
Linfeng Song, Yue Zhang, Zhiguo Wang, and Daniel Gildea. 2018 · 2018
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Emily Alsentzer, Samuel Finlayson, Michelle Li, and Marinka Zitnik. 2020 · 2020
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Superloss: A generic loss for robust curriculum learning
Thibault Castells, Philippe Weinzaepfel, and Jerome Revaud. 2020 · 2020
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang. 2020 · 2020
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Distance encoding: Design provably more powerful neural networks for graph representation learning
Pan Li, Yanbang Wang, Hongwei Wang, and Jure Leskovec. 2020 · 2020
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Story forest: Extracting events and telling stories from breaking news
Bang Liu, Fred X Han, Di Niu, Linglong Kong, Kunfeng Lai, and Yu Xu. 2020 · 2020
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Bertscore: Evaluating text generation with BERT
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020a · 2020
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Curriculum learning by dynamic instance hardness
Tianyi Zhou, Shengjie Wang, and Jeff A Bilmes. 2020 · 2020
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Attentive multiview text representation for differential diagnosis
Hadi Amiri, Mitra Mohtarami, and Isaac Kohane. 2021 · 2021
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The human phenotype ontology in 2021
Sebastian Köhler, Michael Gargano, Nicolas Matentzoglu, Leigh C Carmody, David Lewis-Smith, Nicole A Vasilevsky, Daniel Danis, Ganna Balagura, Gareth Baynam, Amy M Brower, et al. 2021 · 2021
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Multi-scale attributed node embedding
Benedek Rozemberczki, Carl Allen, and Rik Sarkar. 2021 · 2021
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Curgraph: Curriculum learning for graph classification
Yiwei Wang, Wei Wang, Yuxuan Liang, Yujun Cai, and Bryan Hooi. 2021 · 2021
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