Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Kalainathan, Diviyan"'
Autor:
Kalainathan, Diviyan, Goudet, Olivier
This paper presents a new open source Python framework for causal discovery from observational data and domain background knowledge, aimed at causal graph and causal mechanism modeling. The 'cdt' package implements the end-to-end approach, recovering
Externí odkaz:
http://arxiv.org/abs/1903.02278
A new causal discovery method, Structural Agnostic Modeling (SAM), is presented in this paper. Leveraging both conditional independencies and distributional asymmetries, SAM aims to find the underlying causal structure from observational data. The ap
Externí odkaz:
http://arxiv.org/abs/1803.04929
Autor:
Goudet, Olivier, Kalainathan, Diviyan, Caillou, Philippe, Guyon, Isabelle, Lopez-Paz, David, Sebag, Michèle
We present Causal Generative Neural Networks (CGNNs) to learn functional causal models from observational data. CGNNs leverage conditional independencies and distributional asymmetries to discover bivariate and multivariate causal structures. CGNNs m
Externí odkaz:
http://arxiv.org/abs/1711.08936
Autor:
Goudet, Olivier, Kalainathan, Diviyan, Caillou, Philippe, Guyon, Isabelle, Lopez-Paz, David, Sebag, Michèle
We introduce a new approach to functional causal modeling from observational data, called Causal Generative Neural Networks (CGNN). CGNN leverages the power of neural networks to learn a generative model of the joint distribution of the observed vari
Externí odkaz:
http://arxiv.org/abs/1709.05321
Akademický článek
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Autor:
Kalainathan, Diviyan
Publikováno v:
Artificial Intelligence [cs.AI]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLS516⟩
Machine Learning [stat.ML]. Université Paris Sud (Paris 11)-Université Paris Saclay, 2019. English
Machine Learning [stat.ML]. Université Paris Sud (Paris 11)-Université Paris Saclay, 2019. English. ⟨NNT : ⟩
Machine Learning [stat.ML]. Université Paris Sud (Paris 11)-Université Paris Saclay, 2019. English
Machine Learning [stat.ML]. Université Paris Sud (Paris 11)-Université Paris Saclay, 2019. English. ⟨NNT : ⟩
Causal discovery is of utmost importance for agents who must plan, reason and decide based on observations; where mistaking correlation with causation might lead to unwanted consequences. The gold standard to discover causal relations is to perform e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5e255de8b753a837e989fb6229ca0d29
https://tel.archives-ouvertes.fr/tel-02528204/file/88421_KALAINATHAN_2019_archivage.pdf
https://tel.archives-ouvertes.fr/tel-02528204/file/88421_KALAINATHAN_2019_archivage.pdf
Publikováno v:
NeurIPS 2019-33th Annual Conference on Neural Information Processing Systems
NeurIPS 2019-33th Annual Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada
NeurIPS 2019-33th Annual Conference on Neural Information Processing Systems, Dec 2019, Vancouver, Canada
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::ddd3276f17d14f779bbde93d49ce54db
https://hal.inria.fr/hal-02415639/document
https://hal.inria.fr/hal-02415639/document
Akademický článek
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.
Autor:
Kalainathan, Diviyan
Publikováno v:
Machine Learning [stat.ML]. Université Paris Sud (Paris 11)-Université Paris Saclay, 2019. English
Artificial Intelligence [cs.AI]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLS516⟩
Artificial Intelligence [cs.AI]. Université Paris Saclay (COmUE), 2019. English. ⟨NNT : 2019SACLS516⟩
Causal discovery is of utmost importance for agents who must plan, reason and decide based on observations; where mistaking correlation with causation might lead to unwanted consequences. The gold standard to discover causal relations is to perform e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::b545d65bccfdbafc2854c849757b0eff
https://theses.hal.science/tel-02528204
https://theses.hal.science/tel-02528204
Autor:
Midler, Estelle, Bellec, Thierry, Isabelle, Burens, Nicolas, Deffontaines, Hostiou, Nathalie, Jacques-Jouvenot, Dominique, Nicot, Anne-Marie, Kalainathan, Diviyan, Agri, Actif
Publikováno v:
Actif’Agri. Transformations des emplois et des activités en agriculture
Actif’Agri. Transformations des emplois et des activités en agriculture, 2019
Actif’Agri. Transformations des emplois et des activités en agriculture, 2019
International audience; Les travailleurs agricoles sont exposés à des risques physiques, chimiques et biologiques ainsi qu’à de fortes contraintes d’organisation de leur temps de travail. Ils sont également plus souvent touchés par les accid
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::9fbec158b2dd912da5bae9eebd6e90fe
https://hal.inrae.fr/hal-02534832
https://hal.inrae.fr/hal-02534832