@@ -220,24 +220,24 @@ @inproceedings{daw2021pid
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pdf ={ https://arxiv.org/abs/2106.02993} ,
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preview ={ pidgan.png}
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}
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- ## changed inbook to inproceedings
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+ changed inbook to inproceedings
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- ## @article {doi:10.1089/big.2020.0071 ,
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- ## author = { Muralidhar, Nikhil and Bu, Jie and Cao, Ze and He, Long and Ramakrishnan, Naren and Tafti, Danesh and Karpatne, Anuj} ,
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- ## title = { Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems} ,
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- ## journal = { Big Data} ,
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- ## volume = { 8} ,
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- ## number = { 5} ,
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- ## pages = { 431-449} ,
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- ## year = { 2020} ,
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- ## doi = { 10.1089/big.2020.0071} ,
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- ## note ={ PMID: 33090021} ,
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- ## URL = { https://doi.org/10.1089/big.2020.0071} ,
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- ## eprint = { https://doi.org/10.1089/big.2020.0071} ,
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- ## abbr ={ Big Data} ,
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- ## pdf ={ https://www.liebertpub.com/doi/full/10.1089/big.2020.0071} ,
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- ## preview ={ phynet.png}
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- ## }
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+ @article {doi:10.1089/big.2020.0071 ,
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+ author = { Muralidhar, Nikhil and Bu, Jie and Cao, Ze and He, Long and Ramakrishnan, Naren and Tafti, Danesh and Karpatne, Anuj} ,
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+ title = { Physics-Guided Deep Learning for Drag Force Prediction in Dense Fluid-Particulate Systems} ,
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+ journal = { Big Data} ,
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+ volume = { 8} ,
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+ number = { 5} ,
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+ pages = { 431-449} ,
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+ year = { 2020} ,
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+ doi = { 10.1089/big.2020.0071} ,
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+ note ={ PMID: 33090021} ,
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+ URL = { https://doi.org/10.1089/big.2020.0071} ,
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+ eprint = { https://doi.org/10.1089/big.2020.0071} ,
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+ abbr ={ Big Data} ,
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+ pdf ={ https://www.liebertpub.com/doi/full/10.1089/big.2020.0071} ,
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+ preview ={ phynet.png}
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+ }
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@article {papakis2020gcnnmatch ,
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title ={ Gcnnmatch: Graph convolutional neural networks for multi-object tracking via sinkhorn normalization} ,
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