{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,6]],"date-time":"2024-09-06T01:50:31Z","timestamp":1725587431484},"reference-count":26,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,9,1]],"date-time":"2020-09-01T00:00:00Z","timestamp":1598918400000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,9]]},"DOI":"10.1109\/mlsp49062.2020.9231794","type":"proceedings-article","created":{"date-parts":[[2020,10,21]],"date-time":"2020-10-21T17:53:19Z","timestamp":1603302799000},"page":"1-6","source":"Crossref","is-referenced-by-count":1,"title":["Graph Topology Inference Benchmarks for Machine Learning"],"prefix":"10.1109","author":[{"given":"Carlos","family":"Lassance","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vincent","family":"Gripon","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gonzalo","family":"Mateos","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1007\/s10791-015-9268-9"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00521"},{"journal-title":"Improved visual localization via graph smoothing","year":"2019","author":"lassance","key":"ref12"},{"journal-title":"Exploiting unsupervised inputs for accurate few-shot classification","year":"2020","author":"hu","key":"ref13"},{"key":"ref14","article-title":"Influential sample selection: A graph signal processing approach","author":"anirudh","year":"2017","journal-title":"Tech Rep"},{"journal-title":"Open graph benchmark Datasets for machine learning on graphs","year":"2020","author":"hu","key":"ref15"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1016\/j.neuroimage.2019.116276"},{"key":"ref17","article-title":"A fair comparison of graph neural networks for graph classification","author":"errica","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1145\/1553374.1553511"},{"key":"ref19","article-title":"Simplifying graph convolutional networks","author":"wu","year":"0","journal-title":"International Conference on Machine Learning"},{"key":"ref4","article-title":"Characterization and inference of graph diffusion processes from observations of stationary signals","author":"pasdeloup","year":"2017","journal-title":"IEEE Transactions on Signal and Information Processing over Networks"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1073\/pnas.0506580102"},{"journal-title":"Graph construction from data using non negative kernel regression (NNK graphs)","year":"2019","author":"shekkizhar","key":"ref6"},{"key":"ref5","article-title":"Large scale graph learning from smooth signals","author":"kalofolias","year":"0","journal-title":"International Conference on Learning Representations"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1109\/JSTSP.2017.2726975"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2018.2890143"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1609\/aimag.v29i3.2157"},{"key":"ref9","article-title":"Identifying the topology of undirected networks from diffused non-stationary graph signals","author":"shafipour","year":"2018","journal-title":"IEEE Transactions on Signal Processing"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/JPROC.2018.2798928"},{"key":"ref20","article-title":"On the choice of graph neural network architectures","author":"vignac","year":"0","journal-title":"ICASSP 2020 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1109\/ICVGIP.2008.47"},{"key":"ref21","article-title":"Efficient approximation and denoising of graph signals using the multiscale basis dictionaries","author":"irion","year":"2016","journal-title":"IEEE Transactions on Signal and Information Processing over Networks"},{"key":"ref24","doi-asserted-by":"publisher","DOI":"10.1145\/2733373.2806390"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.308"},{"journal-title":"GSP-BOX A toolbox for signal processing on graphs","year":"2014","author":"perraudin","key":"ref26"},{"key":"ref25","article-title":"Knowl-edge transfer from weakly labeled audio using convolutional neural network for sound events and scenes","author":"kumar","year":"0","journal-title":"2018 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP)"}],"event":{"name":"2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP)","start":{"date-parts":[[2020,9,21]]},"location":"Espoo, Finland","end":{"date-parts":[[2020,9,24]]}},"container-title":["2020 IEEE 30th International Workshop on Machine Learning for Signal Processing (MLSP)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9217888\/9231523\/09231794.pdf?arnumber=9231794","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:52:58Z","timestamp":1656453178000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9231794\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,9]]},"references-count":26,"URL":"https:\/\/doi.org\/10.1109\/mlsp49062.2020.9231794","relation":{},"subject":[],"published":{"date-parts":[[2020,9]]}}}