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Results by year

Table representation of search results timeline featuring number of search results per year.

Year Number of Results
1801 1
1806 1
1815 1
1838 1
1847 1
1850 1
1851 1
1852 1
1854 1
1855 1
1857 3
1858 2
1859 6
1860 5
1861 1
1862 3
1866 1
1867 2
1871 4
1872 4
1873 3
1874 8
1875 17
1876 1
1877 2
1879 3
1881 2
1882 10
1883 11
1884 7
1885 4
1886 3
1887 3
1888 15
1889 13
1890 4
1891 3
1892 2
1894 2
1895 3
1896 7
1897 3
1898 4
1899 5
1901 2
1904 1
1907 1
1908 2
1909 2
1910 3
1911 2
1912 2
1913 4
1914 12
1915 13
1916 9
1917 5
1918 2
1919 1
1920 6
1921 4
1922 3
1923 2
1924 6
1925 5
1926 3
1927 9
1928 6
1929 6
1930 9
1932 3
1933 3
1935 1
1936 9
1937 1
1938 1
1939 4
1940 1
1941 3
1942 5
1943 2
1944 2
1945 9
1946 9
1947 6
1948 17
1949 16
1950 20
1951 15
1952 16
1953 27
1954 16
1955 33
1956 23
1957 20
1958 26
1959 29
1960 21
1961 35
1962 38
1963 71
1964 45
1965 55
1966 88
1967 83
1968 112
1969 130
1970 130
1971 143
1972 155
1973 133
1974 154
1975 801
1976 884
1977 826
1978 877
1979 947
1980 952
1981 1019
1982 1105
1983 1291
1984 1356
1985 1376
1986 1464
1987 1467
1988 1649
1989 2041
1990 2143
1991 2262
1992 2318
1993 2445
1994 2373
1995 2585
1996 2806
1997 2895
1998 2999
1999 3298
2000 3650
2001 3751
2002 3952
2003 4308
2004 4669
2005 5361
2006 5599
2007 6006
2008 6519
2009 7185
2010 7669
2011 8321
2012 9076
2013 9760
2014 10371
2015 10899
2016 11195
2017 11643
2018 12266
2019 12811
2020 14968
2021 17107
2022 17561
2023 16694
2024 5632

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Search Results

247,641 results

Results by year

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Page 1
ICON: Learning Regular Maps Through Inverse Consistency.
Greer H, Kwitt R, Vialard FX, Niethammer M. Greer H, et al. Proc IEEE Int Conf Comput Vis. 2021 Oct;2021:3376-3385. doi: 10.1109/iccv48922.2021.00338. Proc IEEE Int Conf Comput Vis. 2021. PMID: 35355618 Free PMC article.
We explore if it is possible to obtain spatial regularity using an inverse consistency loss only and elucidate what explains map regularity in such a context. ...Despite the simplicity of this approach, our experiments present compelling evidence, on both synthetic …
We explore if it is possible to obtain spatial regularity using an inverse consistency loss only and elucidate what explains map r …
Bridged adversarial training.
Kim H, Lee W, Lee S, Lee J. Kim H, et al. Neural Netw. 2023 Oct;167:266-282. doi: 10.1016/j.neunet.2023.08.024. Epub 2023 Aug 22. Neural Netw. 2023. PMID: 37666185
Inspired by the observation, we investigate the effect of different regularizers and discover the negative effect of the smoothness regularizer on maximizing the margin. ...
Inspired by the observation, we investigate the effect of different regularizers and discover the negative effect of the smoothness …
The role of complementary learning systems in learning and consolidation in a quasi-regular domain.
Mirković J, Vinals L, Gaskell MG. Mirković J, et al. Cortex. 2019 Jul;116:228-249. doi: 10.1016/j.cortex.2018.07.015. Epub 2018 Aug 1. Cortex. 2019. PMID: 30149965 Free article.
We examine the role of off-line memory consolidation processes in the learning and retention of a new quasi-regular linguistic system similar to the English past tense. Quasi-regular systems are characterized by a dominance of systematic, regular forms (e.g., …
We examine the role of off-line memory consolidation processes in the learning and retention of a new quasi-regular linguistic system …
Asymmetry Factors Shaping Regular and Irregular Bursting Rhythms in Central Pattern Generators.
Elices I, Varona P. Elices I, et al. Front Comput Neurosci. 2017 Feb 16;11:9. doi: 10.3389/fncom.2017.00009. eCollection 2017. Front Comput Neurosci. 2017. PMID: 28261081 Free PMC article.
The analysis indicates that asymmetric configurations display robust regular rhythms and that large regions of both regular and irregular but coordinated rhythms exist as a function of the asymmetry in the circuit. Our results show that asymmetry both in the maximal …
The analysis indicates that asymmetric configurations display robust regular rhythms and that large regions of both regular an …
Neural entrainment via perceptual inferences.
Tavano A, Maess B, Poeppel D, Schröger E. Tavano A, et al. Eur J Neurosci. 2022 Jun;55(11-12):3277-3287. doi: 10.1111/ejn.15630. Epub 2022 Mar 3. Eur J Neurosci. 2022. PMID: 35193163
Entrainment depends on sequential neural phase reset by regular stimulus onset, a temporal parameter. Entraining to sequences of identical stimuli also entails stimulus feature predictability, but this component is not readily separable from temporal regularity. ... …
Entrainment depends on sequential neural phase reset by regular stimulus onset, a temporal parameter. Entraining to sequences of iden …
From random to regular: neural constraints on the emergence of isochronous rhythm during cultural transmission.
Lumaca M, Haumann NT, Vuust P, Brattico E, Baggio G. Lumaca M, et al. Soc Cogn Affect Neurosci. 2018 Sep 5;13(8):877-888. doi: 10.1093/scan/nsy054. Soc Cogn Affect Neurosci. 2018. PMID: 30016510 Free PMC article.
The cultural evolutionary origins of this feature remain unclear. Here, we test the hypothesis that regularities in the temporal organization of signalling sequences arise in the course of cultural transmission as adaptations to aspects of cortical function. We conducted t …
The cultural evolutionary origins of this feature remain unclear. Here, we test the hypothesis that regularities in the temporal orga …
Plug-and-Play Regularization Using Linear Solvers.
Nair P, Chaudhury KN. Nair P, et al. IEEE Trans Image Process. 2022;31:6344-6355. doi: 10.1109/TIP.2022.3211473. Epub 2022 Oct 14. IEEE Trans Image Process. 2022. PMID: 36215363
Motivated by the recent plug-and-play paradigm for image regularization, we construct a quadratic regularizer whose reconstruction capability is competitive with state-of-the-art regularizers. The novelty of the regularizer is that, unlike classical …
Motivated by the recent plug-and-play paradigm for image regularization, we construct a quadratic regularizer whose reconstruc …
Structured sparsity regularization for analyzing high-dimensional omics data.
Vinga S. Vinga S. Brief Bioinform. 2021 Jan 18;22(1):77-87. doi: 10.1093/bib/bbaa122. Brief Bioinform. 2021. PMID: 32597465 Review.
Beyond the now-classic elastic net, one of the best-known methods that combine lasso with ridge penalizations, we briefly overview recent literature on structured regularizers and penalty functions that have been applied in biomedical data to build parsimonious models in a …
Beyond the now-classic elastic net, one of the best-known methods that combine lasso with ridge penalizations, we briefly overview recent li …
Regularizing transformers with deep probabilistic layers.
Aguilera AC, Olmos PM, Artés-Rodríguez A, Pérez-Cruz F. Aguilera AC, et al. Neural Netw. 2023 Apr;161:565-574. doi: 10.1016/j.neunet.2023.01.032. Epub 2023 Feb 9. Neural Netw. 2023. PMID: 36812832
Language models (LM) have grown non-stop in the last decade, from sequence-to-sequence architectures to attention-based Transformers. However, regularization is not deeply studied in those structures. In this work, we use a Gaussian Mixture Variational Autoencoder (GMVAE) …
Language models (LM) have grown non-stop in the last decade, from sequence-to-sequence architectures to attention-based Transformers. Howeve …
Smoothed-NUV Priors for Imaging.
Ma B, Zalmai N, Loeliger HA. Ma B, et al. IEEE Trans Image Process. 2022;31:4663-4678. doi: 10.1109/TIP.2022.3186749. Epub 2022 Jul 12. IEEE Trans Image Process. 2022. PMID: 35786555
Variations of L1 -regularization including, in particular, total variation regularization, have hugely improved computational imaging. However, sharper edges and fewer staircase artifacts can be achieved with convex-concave regularizers. We present a new clas …
Variations of L1 -regularization including, in particular, total variation regularization, have hugely improved computational …
247,641 results
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