Zobrazeno 1 - 10
of 15
pro vyhledávání: '"Matko Bošnjak"'
Autor:
Nives Skunca, Matko Bošnjak, Anita Kriško, Panče Panov, Sašo Džeroski, Tomislav Smuc, Fran Supek
Publikováno v:
PLoS Computational Biology, Vol 9, Iss 1, p e1002852 (2013)
New microbial genomes are sequenced at a high pace, allowing insight into the genetics of not only cultured microbes, but a wide range of metagenomic collections such as the human microbiome. To understand the deluge of genomic data we face, computat
Externí odkaz:
https://doaj.org/article/6c85640e7fe84f3e95f880e3eabc1903
Publikováno v:
PLoS ONE, Vol 6, Iss 7, p e21800 (2011)
Outcomes of high-throughput biological experiments are typically interpreted by statistical testing for enriched gene functional categories defined by the Gene Ontology (GO). The resulting lists of GO terms may be large and highly redundant, and thus
Externí odkaz:
https://doaj.org/article/8810d369a0334ac7a815bb512de201a8
Publikováno v:
Knowledge Graphs for eXplainable Artificial Intelligence
Reasoning with knowledge expressed in natural language and Knowledge Bases (KBs) is a major challenge for Artificial Intelligence, with applications in machine reading, dialogue, and question answering. General neural architectures that jointly learn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dc0b40ab40d092c1772dbd43ea4ba609
https://doi.org/10.1609/aaai.v34i04.5962
https://doi.org/10.1609/aaai.v34i04.5962
Autor:
Marek Sergot, Lars Buesing, Matko Bošnjak, Pushmeet Kohli, Kevin Ellis, David Pfau, Richard Evans
Publikováno v:
Artificial Intelligence. 299:103521
How should a machine intelligence perform unsupervised structure discovery over streams of sensory input? One approach to this problem is to cast it as an apperception task [1] . Here, the task is to construct an explicit interpretable theory that bo
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::aab1d01ff05f359c22c84d585137060a
https://doi.org/10.1016/j.artint.2021.103521
https://doi.org/10.1016/j.artint.2021.103521
Autor:
Jeff Mitchell, Tim Rocktäschel, Sebastian Riedel, Pasquale Minervini, Dirk Weissenborn, Johannes Welbl, Pontus Stenetorp, Matko Bošnjak, Tim Dettmers, Isabelle Augenstein, Thomas Demeester
Publikováno v:
ACL (4)
University of Copenhagen
56th Annual meeting of the Association for Computational Linguistics (ACL 2018) : proceedings of system demonstrations
University of Copenhagen
56th Annual meeting of the Association for Computational Linguistics (ACL 2018) : proceedings of system demonstrations
Many Machine Reading and Natural Language Understanding tasks require reading supporting text in order to answer questions. For example, in Question Answering, the supporting text can be newswire or Wikipedia articles; in Natural Language Inference,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::1830f2aa805bc52cdbb432c6b4e24442
http://arxiv.org/abs/1806.08727
http://arxiv.org/abs/1806.08727
Publikováno v:
SocialNLP@EMNLP
Many current natural language processing applications for social media rely on representation learning and utilize pre-trained word embeddings. There currently exist several publicly-available, pre-trained sets of word embeddings, but they contain fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f2e16059d1a894ec7b16242631296737
Publikováno v:
Discovery Science ISBN: 9783319118116
Discovery Science
Scopus-Elsevier
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Discovery Science
Discovery Science
Scopus-Elsevier
Lecture Notes in Computer Science
Lecture Notes in Computer Science-Discovery Science
Personalized recommender systems rely on each user’s personal usage data in the system, in order to assist in decision making. However, privacy policies protecting users’ rights prevent these highly personal data from being publicly available to
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::41f1b35cd8beb06953d8f1ce9813f46f
https://www.bib.irb.hr/755830
https://www.bib.irb.hr/755830
Publikováno v:
Proceedings of the ACL 2014 Workshop on Semantic Parsing.
Many machine reading approaches, from shallow information extraction to deep semantic parsing, map natural language to symbolic representations of meaning. Representations such as first-order logic capture the richness of natural language and support
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::dc1e1fdebaa395bda10a3c7738f9ed64
https://doi.org/10.3115/v1/w14-2409
https://doi.org/10.3115/v1/w14-2409
Publikováno v:
SAC
It is difficult to determine the country of origin of the author of a short message based only on the text. This is an even more complex problem when more than one country uses the same native language. In this paper, we address the specific problem
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d321416f6620ff43fe10b9cb262a2c02
https://doi.org/10.1145/2480362.2480535
https://doi.org/10.1145/2480362.2480535
Autor:
Christine A. Orengo, Liang Lan, Daniel W. A. Buchan, Jeffrey M. Yunes, Alberto Paccanaro, Yannick Mahlich, Enrico Lavezzo, Patricia C. Babbitt, Domenico Cozzetto, Cedric Landerer, Jari Björne, Esmeralda Vicedo, Robert Rentzsch, Rajendra Joshi, Hagit Shatkay, Nives Škunca, Zheng Wang, Tal Ronnen Oron, Ingolf Sommer, Amos Marc Bairoch, Mark Heron, Panče Panov, Daisuke Kihara, Wyatt T. Clark, Michael J.E. Sternberg, Steven E. Brenner, Sašo Džeroski, Burkhard Rost, Christian Schaefer, Karin Verspoor, Harshal Inamdar, Tapio Salakoski, Meghana Chitale, Alfonso E. Romero, Julian Gough, Fran Supek, Olivier Lichtarge, Dominik Achten, Serkan Erdin, Michael Kiening, Petri Törönen, Avik Datta, Iddo Friedberg, Thomas A. Hopf, Liisa Holm, Rita Casadio, Asa Ben-Hur, Tatjana Braun, Sean D. Mooney, Marco Falda, Kiley Graim, Michal Linial, Alexandra M. Schnoes, Christopher S. Funk, Rebecca Kaßner, Patrik Koskinen, Nemanja Djuric, Paolo Fontana, Predrag Radivojac, Tobias Wittkop, Kevin Bryson, Maximilian Hecht, Susanna Repo, Haixuan Yang, Artem Sokolov, Prajwal Bhat, Tobias Hamp, Jianlin Cheng, Mark N. Wass, Gaurav Pandey, Michael L Souza, Damiano Piovesan, Ameet Talwalkar, Stefan Seemayer, Eric Venner, Sunitha K Manjari, Fanny Gatzmann, Aalt D. J. van Dijk, Manfred Roos, Tomislav Šmuc, David T. Jones, Peter Hönigschmid, Ariane Boehm, Florian Auer, Jussi Nokso-Koivisto, Stefano Toppo, Slobodan Vucetic, Denis Krompass, Qingtian Gong, Cajo J. F. ter Braak, Andrew Wong, Barbara Di Camillo, Yiannis A. I. Kourmpetis, Andreas Martin Lisewski, Matko Bošnjak, Bhakti Limaye, Weidong Tian, Yuhong Guo, Xinran Dong, Hai Fang, Yuanpeng Zhou, Stefanie Kaufmann
Publikováno v:
Nature Methods
Nature methods
Nature Methods : techniques for life scientists and chemists 10 (2013)
Nature Methods : techniques for life scientists and chemists, 10, 221-227
Nature Methods, Vol. 10, No 3 (2013) pp. 221-7
Nature methods
Nature Methods : techniques for life scientists and chemists 10 (2013)
Nature Methods : techniques for life scientists and chemists, 10, 221-227
Nature Methods, Vol. 10, No 3 (2013) pp. 221-7
Automated annotation of protein function is challenging. As the number of sequenced genomes rapidly grows, the overwhelming majority of protein products can only be annotated computationally. If computational predictions are to be relied upon, it is
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::c19e166af084819ee544097527791f10
http://hdl.handle.net/10449/22010
http://hdl.handle.net/10449/22010