{"id":664,"date":"2024-05-24T14:27:29","date_gmt":"2024-05-24T14:27:29","guid":{"rendered":"https:\/\/deel.quebec\/publications\/"},"modified":"2024-05-24T14:32:09","modified_gmt":"2024-05-24T14:32:09","slug":"publications","status":"publish","type":"page","link":"https:\/\/deel.quebec\/en\/publications\/","title":{"rendered":"Publications"},"content":{"rendered":"<h2><strong>2024<\/strong><\/h2>\n<h6><\/h6>\n<h6><strong>Journal articles<\/strong><\/h6>\n<ul>\n<li><strong><a href=\"https:\/\/hal.science\/hal-04480870\">Tackling the XAI Disagreement Problem with Regional Explanations<\/a><\/strong><\/li>\n<\/ul>\n<p>Gabriel Laberge, Yann Pequignot, Mario Marchand, Foutse Khomh<\/p>\n<p><em>International Conference on Artificial Intelligence and Statistics (AISTATS)<\/em>, May 2024, Valencia, Spain.<strong>\u00a0<\/strong><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255315v2\"><strong>Oblivious Turing Machine<\/strong><\/a><\/li>\n<\/ul>\n<p>Sofiane Azogagh, Victor Delfour, Marc-Olivier Killijian<\/p>\n<p><em>19th European Dependable Computing Conference<\/em>, Apr 2024, Leuven, France<\/p>\n<p>&nbsp;<\/p>\n<h6><\/h6>\n<h6><strong>Preprints, Working Papers, &#8230;<\/strong><\/h6>\n<ul>\n<li><strong><a href=\"https:\/\/hal.science\/hal-04533467\">Layerwise Early Stopping for Test Time Adaptation<\/a><\/strong><\/li>\n<\/ul>\n<p>Sabyasachi Sahoo, Mostafa Elaraby, Jonas Ngnawe, Yann Pequignot, Fr\u00e9d\u00e9ric Precioso, Christian Gagn\u00e9,2024<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>2023<\/strong><\/h2>\n<h6><\/h6>\n<h6><strong>Journal articles<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04314171\"><strong>Silent bugs in deep learning frameworks: an empirical study of Keras and TensorFlow<\/strong><\/a><\/li>\n<\/ul>\n<p>Florian Tambon, Amin Nikanjam, Le An, Foutse Khomh, Giuliano Antoniol<\/p>\n<p><em>Empirical Software Engineering<\/em>, 2023, 29 (1), pp.10.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1007\/s10664-023-10389-6\">\u27e810.1007\/s10664-023-10389-6\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255009\"><strong>Physics-Guided Adversarial Machine Learning for Aircraft Systems Simulation<\/strong><\/a><\/li>\n<\/ul>\n<p>Houssem Ben Braiek, Thomas Reid, Foutse Khomh,<em>IEEE Transactions on Reliability<\/em>, 2023, 72 (3), pp.1161-1175.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1109\/TR.2022.3196272\">\u27e810.1109\/TR.2022.3196272\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04214225\"><strong>Bugs in machine learning-based systems: a faultload benchmark<\/strong><\/a><\/li>\n<\/ul>\n<p>Mohammad Mehdi Morovati, Amin Nikanjam, Foutse Khomh, Zhen Ming Jiang<\/p>\n<p><em>Empirical Software Engineering<\/em>, 2023, 28 (3), pp.62.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1007\/s10664-023-10291-1\">\u27e810.1007\/s10664-023-10291-1\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04204205\"><strong>Behavioural equivalences for continuous-time Markov processes<\/strong><\/a><\/li>\n<\/ul>\n<p>Linan Chen, Florence Clerc, Prakash Panangaden<\/p>\n<p><em>Mathematical Structures in Computer Science<\/em>, 2023, 33 (4-5), pp.222-258.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1017\/S0960129523000099\">\u27e810.1017\/S0960129523000099\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04198229\"><strong>A probabilistic framework for mutation testing in deep neural networks<\/strong><\/a><\/li>\n<\/ul>\n<p>Florian Tambon, Foutse Khomh, Giuliano Antoniol<\/p>\n<p><em>Information and Software Technology<\/em>, 2023, 155 (2), pp.107129.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1016\/j.infsof.2022.107129\">\u27e810.1016\/j.infsof.2022.107129\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04214239\"><strong>Bug Characterization in Machine Learning-based Systems<\/strong><\/a><\/li>\n<\/ul>\n<p>Mohammad Mehdi Morovati, Amin Nikanjam, Florian Tambon, Foutse Khomh, Zhen Ming <em>Empirical Software Engineering<\/em>, 2023,\u00a0<a href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2307.14512\">\u27e810.48550\/arXiv.2307.14512\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255231\"><strong>Explainable prediction of Qcodes for NOTAMs using column generation<\/strong><\/a><\/li>\n<\/ul>\n<p>Krunal Kishor Patel, Guy Desaulniers, Andrea Lodi, Freddy Lecue<\/p>\n<p><em>Journal of the Operational Research Society<\/em>, 2023, pp.1-11.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1080\/01605682.2023.2181715\">\u27e810.1080\/01605682.2023.2181715\u27e9<\/a><\/p>\n<h6><\/h6>\n<h6><strong>Conference papers<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04233547\"><strong>Statistical Guarantees for Variational Autoencoders using PAC-Bayesian Theory<\/strong><\/a><\/li>\n<\/ul>\n<p>Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain<\/p>\n<p><em>37th Conference on Neural Information Processing Systems (NeurIPS 2023).<\/em>, Dec 2023, New-Orleans, United States<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04204203\"><strong>PAC-Bayesian Generalization Bounds for Adversarial Generative Models<\/strong><\/a><\/li>\n<\/ul>\n<p>Sokhna Diarra Mbacke, Florence Clerc, Pascal Germain<\/p>\n<p><em>International Conference on Machine Learning<\/em>, Jul 2023, Honololu, Hawaii, United States<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04232192\"><strong>Fool SHAP with Stealthily Biased Sampling<\/strong><\/a><\/li>\n<\/ul>\n<p>Gabriel Laberge, Ulrich A\u00efvodji, Satoshi Hara, Mario Marchand, Foutse Khomh<\/p>\n<p><em>International Conference on Learning Representations (ICLR)<\/em>, May 2023, Kigali, Rwanda<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255241\"><strong>Estimating Regression Predictive Distributions with Sample Networks<\/strong><\/a><\/li>\n<\/ul>\n<p>Ali Harakeh, Jordan Sir Kwang Hu, Naiqing Guan, Steven Waslander, Liam Paull<\/p>\n<p><em>Proceedings of the AAAI Conference on Artificial Intelligence<\/em>, Feb 2023, Washington DC, United States. pp.7830-7838,\u00a0<a href=\"https:\/\/dx.doi.org\/10.1609\/aaai.v37i6.25948\">\u27e810.1609\/aaai.v37i6.25948\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<h6><\/h6>\n<h6><strong>Proceedings<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04222495\"><strong>Sample Boosting Algorithm (SamBA) -An Interpretable Greedy Ensemble Classifier Based On Local Expertise For Fat Data<\/strong><\/a><\/li>\n<\/ul>\n<p>Baptiste Bauvin, C\u00e9cile Capponi, Florence Clerc, Pascal Germain, Sokol Ko\u00e7o, Jacques Corbeil<\/p>\n<p><em>Proceedings of Machine Learning Research<\/em>, 216, pp.130-140, 2023, Proceedings of the Thirty-Ninth Conference on Uncertainty in Artificial Intelligence<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04198231\"><strong>Mutation Testing of Deep Reinforcement Learning Based on Real Faults<\/strong><\/a><\/li>\n<\/ul>\n<p>Florian Tambon, Vahid Majdinasab, Amin Nikanjam, Foutse Khomh, Giuliano Antoniol<\/p>\n<p>IEEE, pp.188-198, 2023,\u00a0<a href=\"https:\/\/dx.doi.org\/10.1109\/ICST57152.2023.00026\">\u27e810.1109\/ICST57152.2023.00026\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<h6><\/h6>\n<h6><strong>Preprints, Working Papers, &#8230;<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255457\"><strong>Deploying Deep Reinforcement Learning Systems: A Taxonomy of Challenges<\/strong><\/a><\/li>\n<\/ul>\n<p>Ahmed Haj Yahmed, Altaf Allah Abbassi, Amin Nikanjam, Heng Li, Foutse Khomh 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255459\"><strong>An Intentional Forgetting-Driven Self-Healing Method For Deep Reinforcement Learning Systems<\/strong><\/a><\/li>\n<\/ul>\n<p>Ahmed Haj Yahmed, Rached Bouchoucha, Houssem Ben Braiek, Foutse Khomh, 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255315\"><strong>Oblivious Turing Machine<\/strong><\/a><\/li>\n<\/ul>\n<p>Sofiane Azogagh, Victor Delfour, Marc-Olivier Killijian 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255252\"><strong>HOMRS: High Order Metamorphic Relations Selector for Deep Neural Networks<\/strong><\/a><\/li>\n<\/ul>\n<p>Florian Tambon, Giulio Antoniol, Foutse Khomh 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04236058\"><strong>RKHS Weightings of Functions<\/strong><\/a><\/li>\n<\/ul>\n<p>Gabriel Dub\u00e9, Mario Marchand 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04232220\"><strong>Understanding Interventional TreeSHAP : How and Why it Works<\/strong><\/a><\/li>\n<\/ul>\n<p>Gabriel Laberge, Yann Batiste Pequignot 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04232199\"><strong>Partial Order in Chaos: Consensus on Feature Attributions in the Rashomon Set<\/strong><\/a><\/li>\n<\/ul>\n<p>Gabriel Laberge, Yann Pequignot, Foutse Khomh, Mario Marchand, Alexandre Mathieu, 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04221896\"><strong>Crypto&#8217;Graph: Leveraging Privacy-Preserving Distributed Link Prediction for Robust Graph Learning<\/strong><\/a><\/li>\n<\/ul>\n<p>Sofiane Azogagh, Zelma Aubin Birba, S\u00e9bastien Gambs, Marc-Olivier Killijian, 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04204206\"><strong>Out-of-distribution detection for regression tasks: parameter versus predictor entropy<\/strong><\/a><\/li>\n<\/ul>\n<p>Yann Pequignot, Mathieu Alain, Patrick Dallaire, Alireza Yeganehparast, Pascal Germain, Jos\u00e9e Desharnais, Fran\u00e7ois Laviolette\u00a02023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04203296\"><strong>Revisiting column-generation-based matheuristic for learning classification trees<\/strong><\/a><\/li>\n<\/ul>\n<p>Krunal Kishor Patel, Guy Desaulniers, Andrea Lodi 2023<\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04010590\"><strong>Learning Hybrid Interpretable Models: Theory, Taxonomy, and Methods<\/strong><\/a><\/li>\n<\/ul>\n<p>Julien Ferry, Gabriel Laberge, Ulrich A\u00efvodji 2023<\/p>\n<p>&nbsp;<\/p>\n<h2><strong>2022<\/strong><\/h2>\n<h6><\/h6>\n<h6><strong>Journal articles<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04254989\"><strong>DiverGet: a Search-Based Software Testing approach for Deep Neural Network Quantization assessment<\/strong><\/a><\/li>\n<\/ul>\n<p>Ahmed Haj Yahmed, Houssem Ben Braiek, Foutse Khomh, Sonia Bouzidi, Rania Zaatour<\/p>\n<p><em>Empirical Software Engineering<\/em>, 2022, 27 (7), pp.193.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1007\/s10664-022-10202-w\">\u27e810.1007\/s10664-022-10202-w\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04203088\"><strong>PROBONITE: PRivate One-Branch-Only Non-Interactive decision Tree Evaluation<\/strong><\/a><\/li>\n<\/ul>\n<p>Sofiane Azogagh, Victor Delfour, S\u00e9bastien Gambs, Marc-Olivier Killijian<\/p>\n<p><em>WAHC&#8217;22: Proceedings of the 10th Workshop on Encrypted Computing &amp; Applied Homomorphic Cryptography<\/em>, 2022, pp.23-33.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1145\/3560827.3563377\">\u27e810.1145\/3560827.3563377\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04194063\"><strong>How to certify machine learning based safety-critical systems? A systematic literature review<\/strong><\/a><\/li>\n<\/ul>\n<p>Florian Tambon, Gabriel Laberge, Le An, Amin Nikanjam, Paulina Stevia Nouwou Mindom, Yann Pequignot, Foutse Khomh, Giulio Antoniol, Ettore Merlo, Fran\u00e7ois Laviolette<\/p>\n<p><em>Automated Software Engineering<\/em>, 2022, 29 (2), pp.38.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1007\/s10515-022-00337-x\">\u27e810.1007\/s10515-022-00337-x\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255041\"><strong>Faults in deep reinforcement learning programs: a taxonomy and a detection approach<\/strong><\/a><\/li>\n<\/ul>\n<p>Amin Nikanjam, Mohammad Mehdi Morovati, Foutse Khomh, Houssem Ben Braiek<\/p>\n<p><em>Automated Software Engineering<\/em>, 2022, 29 (1), pp.8.\u00a0<a href=\"https:\/\/dx.doi.org\/10.1007\/s10515-021-00313-x\">\u27e810.1007\/s10515-021-00313-x\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<h6><\/h6>\n<h6><strong>Conference papers<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255132\"><strong>Characterizing the risk of fairwashing<\/strong><\/a><\/li>\n<\/ul>\n<p>Ulrich A\u00efvodji, Hiromi Arai, S\u00e9bastien Gambs, Satoshi Hara<\/p>\n<p><em>Advances in Neural Information Processing Systems 34 (NeurIPS 2021)<\/em>, Dec 2022, New Orleans (Louisiana), United States. pp.14822&#8211;14834,\u00a0<a href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2106.07504\">\u27e810.48550\/arXiv.2106.07504\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04254999\"><strong>SmOOD: Smoothness-based Out-of-Distribution Detection Approach for Surrogate Neural Networks in Aircraft Design<\/strong><\/a><\/li>\n<\/ul>\n<p>Houssem Ben Braiek, Ali Tfaily, Foutse Khomh, Thomas Reid, Ciro Guida<\/p>\n<p><em>ASE &#8217;22: 37th IEEE\/ACM International Conference on Automated Software Engineering<\/em>, Oct 2022, Rochester, MI, United States. pp.1-13,\u00a0<a href=\"https:\/\/dx.doi.org\/10.1145\/3551349.3556936\">\u27e810.1145\/3551349.3556936\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255092\"><strong>An Empirical Study of Challenges in Converting Deep Learning Models<\/strong><\/a><\/li>\n<\/ul>\n<p>Moses Openja, Amin Nikanjam, Ahmed Haj Yahmed, Foutse Khomh, Zhen Ming Jack Jiang<\/p>\n<p><em>2022 IEEE International Conference on Software Maintenance and Evolution (ICSME)<\/em>, Oct 2022, Limassol, Cyprus. pp.13-23,\u00a0<a href=\"https:\/\/dx.doi.org\/10.1109\/ICSME55016.2022.00010\">\u27e810.1109\/ICSME55016.2022.00010\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255246\"><strong>Studying the Practices of Deploying Machine Learning Projects on Docker<\/strong><\/a><\/li>\n<\/ul>\n<p>Moses Openja, Forough Majidi, Foutse Khomh, Bhagya Chembakottu, Heng Li<\/p>\n<p><em>EASE 2022: The International Conference on Evaluation and Assessment in Software Engineering 2022<\/em>, Jun 2022, Gothenburg, Sweden. pp.190-200,\u00a0<a href=\"https:\/\/dx.doi.org\/10.1145\/3530019.3530039\">\u27e810.1145\/3530019.3530039\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04254924\"><strong>Identification of out-of-distribution cases of CNN using class-based surprise adequacy<\/strong><\/a><\/li>\n<\/ul>\n<p>Mira Marhaba, Ettore Merlo, Foutse Khomh, Giuliano Antoniol<\/p>\n<p><em>CAIN &#8217;22: 1st Conference on AI Engineering &#8211; Software Engineering for AI<\/em>, May 2022, Pittsburgh Pennsylvania, United States. pp.39-40,\u00a0<a href=\"https:\/\/dx.doi.org\/10.1145\/3522664.3528617\">\u27e810.1145\/3522664.3528617\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255203\"><strong>Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation<\/strong><\/a><\/li>\n<\/ul>\n<p>Vincent Mai, Kaustubh Mani, Liam Paull,\u00a0<em>International Conference on Learning Representations (ICLR 2022)<\/em>, Apr 2022, Virtual conference, Unknown Region.\u00a0<a href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2201.01666\">\u27e810.48550\/arXiv.2201.01666\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<h2><strong>2021<\/strong><\/h2>\n<h6><\/h6>\n<h6><strong>Journal articles<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-03259176\"><strong>Automatic Fault Detection for Deep Learning Programs Using Graph Transformations<\/strong><\/a><\/li>\n<\/ul>\n<p>Amin Nikanjam, Houssem Ben Braiek, Mohammad Mehdi Morovati, Foutse Khomh<\/p>\n<p><em>ACM Transactions on Software Engineering and Methodology<\/em>, In press<\/p>\n<p>&nbsp;<\/p>\n<p><strong>Conference papers<\/strong><\/p>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04255221\"><strong>Batch Inverse-Variance Weighting: Deep Heteroscedastic Regression<\/strong><\/a><\/li>\n<\/ul>\n<p>Vincent Mai, Waleed Khamies, Liam Paull<\/p>\n<p><em>ICML 2021 Workshop on Uncertainty &amp; Robustness in Deep Learning<\/em>, Jul 2021, Virtual, Unknown Region.\u00a0<a href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2107.04497\">\u27e810.48550\/arXiv.2107.04497\u27e9<\/a><\/p>\n<p>&nbsp;<\/p>\n<h2><strong>2020<\/strong><\/h2>\n<h6><\/h6>\n<h6><strong>Conference papers<\/strong><\/h6>\n<ul>\n<li><a href=\"https:\/\/hal.science\/hal-04254966\"><strong>Models of Computational Profiles to Study the Likelihood of DNN Metamorphic Test Cases<\/strong><\/a><\/li>\n<\/ul>\n<p>Ettore Merlo, Mira Marhaba, Foutse Khomh, Houssem Ben Braiek, Giuliano Antoniol<\/p>\n<p><em>iMLSE 2020 2nd International Workshop on Machine Learning Systems Engineering\u200b \u200b<\/em>, Dec 2020, Singapore, Singapore.\u00a0<a href=\"https:\/\/dx.doi.org\/10.48550\/arXiv.2107.13491\">\u27e810.48550\/arXiv.2107.13491\u27e9<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"2024 Journal articles Tackling the XAI Disagreement Problem with Regional Explanations Gabriel Laberge, Yann Pequignot,","protected":false},"author":3,"featured_media":270,"parent":0,"menu_order":2,"comment_status":"closed","ping_status":"closed","template":"","meta":[],"_links":{"self":[{"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/pages\/664"}],"collection":[{"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/users\/3"}],"replies":[{"embeddable":true,"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/comments?post=664"}],"version-history":[{"count":2,"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/pages\/664\/revisions"}],"predecessor-version":[{"id":669,"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/pages\/664\/revisions\/669"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/media\/270"}],"wp:attachment":[{"href":"https:\/\/deel.quebec\/en\/wp-json\/wp\/v2\/media?parent=664"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}