{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,10,30]],"date-time":"2024-10-30T02:21:04Z","timestamp":1730254864956,"version":"3.28.0"},"reference-count":47,"publisher":"IEEE","license":[{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2022,8,21]],"date-time":"2022-08-21T00:00:00Z","timestamp":1661040000000},"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":[[2022,8,21]]},"DOI":"10.1109\/icpr56361.2022.9956123","type":"proceedings-article","created":{"date-parts":[[2022,11,29]],"date-time":"2022-11-29T19:34:13Z","timestamp":1669750453000},"page":"4448-4455","source":"Crossref","is-referenced-by-count":0,"title":["DAReN: A Collaborative Approach Towards Visual Reasoning And Disentangling"],"prefix":"10.1109","author":[{"given":"Pritish","family":"Sahu","sequence":"first","affiliation":[{"name":"Rutgers University,Department of Computer Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kalliopi","family":"Basioti","sequence":"additional","affiliation":[{"name":"Rutgers University,Department of Computer Science"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vladimir","family":"Pavlovic","sequence":"additional","affiliation":[{"name":"Rutgers University,Department of Computer Science"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"263","reference":[{"article-title":"Disentanglement by nonlinear ica with general incompressible-flow networks (gin)","year":"2020","author":"sorrenson","key":"ref39"},{"key":"ref38","article-title":"Disentangling factors of variations using few labels","author":"locatello","year":"2019","journal-title":"International Conference on Learning Representations"},{"article-title":"Recent advances in autoencoder-based representation learning","year":"2018","author":"tschannen","key":"ref33"},{"article-title":"Relevance factor vae: Learning and identifying disentangled factors","year":"2019","author":"kim","key":"ref32"},{"key":"ref31","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2019.00307"},{"key":"ref30","first-page":"2649","article-title":"Disentangling by factorising","author":"kim","year":"0"},{"key":"ref37","article-title":"Variational inference of disentangled latent concepts from unlabeled observations","author":"kumar","year":"2018","journal-title":"International Conference on Learning Representations"},{"article-title":"A framework for the quantitative evaluation of disentangled representations","year":"0","author":"eastwood","key":"ref36"},{"key":"ref35","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-04167-0"},{"article-title":"Understanding disentangling in ?-vae","year":"2018","author":"burgess","key":"ref34"},{"key":"ref10","first-page":"887","article-title":"What is artificial intelligence? psychometric ai as an answer","author":"bringsjord","year":"2003","journal-title":"IJCAI"},{"key":"ref40","first-page":"2207","article-title":"Variational autoencoders and nonlinear ica: A unifying framework","author":"khemakhem","year":"2020","journal-title":"International Conference on Artificial Intelligence and Statistics"},{"key":"ref11","article-title":"Analogy with qualitative spatial representations can simulate solving raven&#x2019;s progressive matrices","volume":"29","author":"lovett","year":"2007","journal-title":"Proceedings of the Annual Meeting of the Cognitive Science Society"},{"key":"ref12","first-page":"14245","article-title":"Are disentangled representations helpful for abstract visual reasoning?","author":"van steenkiste","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref13","first-page":"511","article-title":"Measuring abstract reasoning in neural networks","author":"barrett","year":"2018","journal-title":"International Conference on Machine Learning"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2019.00546"},{"key":"ref15","first-page":"1","article-title":"Improving generalization for abstract reasoning tasks using disentangled feature representations","author":"steenbrugge","year":"2018","journal-title":"NeurIPS2018 part of 32nd Conference on Neural Information Processing Systems"},{"key":"ref16","doi-asserted-by":"publisher","DOI":"10.1162\/neco.1989.1.4.541"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2016.90"},{"key":"ref18","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2013.50"},{"article-title":"A survey of inductive biases for factorial representation-learning","year":"2016","author":"ridgeway","key":"ref19"},{"key":"ref28","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR46437.2021.01237"},{"key":"ref4","first-page":"451","article-title":"Scrambled adaptive matrices (sam)&#x2013; a new test of eductive ability","volume":"60","author":"klein","year":"2018","journal-title":"Psychol Test Assessment Model"},{"key":"ref27","article-title":"Hierarchical rule induction network for abstract visual reasoning","volume":"2","author":"hu","year":"2020"},{"journal-title":"Raven's Progressive Matrices and Vocabulary Scales","year":"1998","author":"raven","key":"ref3"},{"key":"ref6","article-title":"A bayesian model of rule induction in raven&#x2019;s progressive matrices","volume":"34","author":"little","year":"2012","journal-title":"Proceedings of the Annual Meeting of the Cognitive Science Society"},{"key":"ref29","article-title":"beta-vae: Learning basic visual concepts with a constrained variational framework","author":"higgins","year":"2017","journal-title":"International Conference on Learning Representations"},{"article-title":"Iq of neural networks","year":"2017","author":"hoshen","key":"ref5"},{"key":"ref8","article-title":"A structure-mapping model of raven&#x2019;s progressive matrices","volume":"32","author":"lovett","year":"2010","journal-title":"Proceedings of the Annual Meeting of the Cognitive Science Society"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1037\/rev0000039"},{"key":"ref2","doi-asserted-by":"publisher","DOI":"10.1111\/j.2044-8341.1941.tb00316.x"},{"key":"ref9","doi-asserted-by":"publisher","DOI":"10.1111\/j.1551-6709.2009.01052.x"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1037\/0033-295X.97.3.404"},{"article-title":"dsprites: Disentanglement testing sprites dataset","year":"2017","author":"matthey","key":"ref46"},{"key":"ref20","first-page":"4114","article-title":"Challenging common assumptions in the unsupervised learning of disentangled representations","volume":"97","author":"locatello","year":"2019","journal-title":"Proceedings of the 36th International Conference on Machine Learning ser Proceedings of Machine Learning Research"},{"key":"ref45","first-page":"1929","article-title":"Dropout: a simple way to prevent neural networks from overfitting","volume":"15","author":"srivastava","year":"2014","journal-title":"The Journal of Machine Learning Research"},{"key":"ref22","doi-asserted-by":"publisher","DOI":"10.1609\/aaai.v32i1.11867"},{"key":"ref47","first-page":"15740","article-title":"On&#x00A8; the transfer of inductive bias from simulation to the real world: a new disentanglement dataset","volume":"32","author":"gondal","year":"2019","journal-title":"Advances in neural information processing systems"},{"key":"ref21","first-page":"3581","article-title":"Semi-supervised learning with deep generative models","author":"kingma","year":"2014","journal-title":"Advances in neural information processing systems"},{"article-title":"Group-based learning of disentangled representations with generalizability for novel contents","year":"2018","author":"hosoya","key":"ref42"},{"key":"ref24","doi-asserted-by":"crossref","DOI":"10.1609\/aaai.v28i1.8755","article-title":"Confident reasoning on raven&#x2019;s progressive matrices tests","author":"mcgreggor","year":"2014","journal-title":"Twenty-Eighth AAAI Conference on Artificial Intelligence"},{"key":"ref41","first-page":"6348","article-title":"Weakly-supervised disentanglement without compromises","author":"locatello","year":"2020","journal-title":"International Conference on Machine Learning"},{"key":"ref23","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2014.180"},{"article-title":"Auto-encoding variational bayes","year":"2013","author":"kingma","key":"ref44"},{"key":"ref26","article-title":"Automatic generation of raven&#x2019;s progressive matrices","author":"wang","year":"2015","journal-title":"Twenty-Fourth International Joint Conference on Artificial Intelligence"},{"key":"ref43","article-title":"Weakly supervised disentanglement with guarantees","author":"shu","year":"2019","journal-title":"International Conference on Learning Representations"},{"key":"ref25","first-page":"1576","article-title":"Similarity-based reasoning, raven&#x2019;s matrices, and general intelligence","author":"mekik","year":"2018","journal-title":"IJCAI"}],"event":{"name":"2022 26th International Conference on Pattern Recognition (ICPR)","start":{"date-parts":[[2022,8,21]]},"location":"Montreal, QC, Canada","end":{"date-parts":[[2022,8,25]]}},"container-title":["2022 26th International Conference on Pattern Recognition (ICPR)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9956007\/9955631\/09956123.pdf?arnumber=9956123","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,19]],"date-time":"2022-12-19T20:03:57Z","timestamp":1671480237000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9956123\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,8,21]]},"references-count":47,"URL":"https:\/\/doi.org\/10.1109\/icpr56361.2022.9956123","relation":{},"subject":[],"published":{"date-parts":[[2022,8,21]]}}}