8 Publications

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[8]
2018 | Journal Article | IST-REx-ID: 563   OA
Ringbauer H, Kolesnikov A, Field D, Barton NH. Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. 2018;208(3):1231-1245. doi:10.1534/genetics.117.300638
View | Files available | DOI | Download (ext.)
 
[7]
2018 | Thesis | IST-REx-ID: 197   OA
Kolesnikov A. Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. IST Austria; 2018. doi:10.15479/AT:ISTA:th_1021
View | Files available | DOI
 
[6]
2017 | Conference Paper | IST-REx-ID: 911   OA
Royer A, Kolesnikov A, Lampert C. Probabilistic image colorization. In: BMVA Press.
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[5]
2017 | Conference Paper | IST-REx-ID: 1000   OA
Kolesnikov A, Lampert C. PixelCNN models with auxiliary variables for natural image modeling. In: Vol 70. Omnipress; 2017:1905-1914.
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[4]
2017 | Conference Paper | IST-REx-ID: 998   OA
Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587
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[3]
2016 | Conference Paper | IST-REx-ID: 1369   OA
Kolesnikov A, Lampert C. Seed, expand and constrain: Three principles for weakly-supervised image segmentation. In: Vol 9908. Springer; 2016:695-711. doi:10.1007/978-3-319-46493-0_42
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[2]
2016 | Conference Paper | IST-REx-ID: 1102   OA
Kolesnikov A, Lampert C. Improving weakly-supervised object localization by micro-annotation. In: Proceedings of the British Machine Vision Conference 2016. Vol 2016-September. BMVA Press; 2016:92.1-92.12. doi:10.5244/C.30.92
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[1]
2014 | Conference Paper | IST-REx-ID: 2171   OA
Kolesnikov A, Guillaumin M, Ferrari V, Lampert C. Closed-form approximate CRF training for scalable image segmentation. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T, eds. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8691. Springer; 2014:550-565. doi:10.1007/978-3-319-10578-9_36
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8 Publications

Mark all

[8]
2018 | Journal Article | IST-REx-ID: 563   OA
Ringbauer H, Kolesnikov A, Field D, Barton NH. Estimating barriers to gene flow from distorted isolation-by-distance patterns. Genetics. 2018;208(3):1231-1245. doi:10.1534/genetics.117.300638
View | Files available | DOI | Download (ext.)
 
[7]
2018 | Thesis | IST-REx-ID: 197   OA
Kolesnikov A. Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images. IST Austria; 2018. doi:10.15479/AT:ISTA:th_1021
View | Files available | DOI
 
[6]
2017 | Conference Paper | IST-REx-ID: 911   OA
Royer A, Kolesnikov A, Lampert C. Probabilistic image colorization. In: BMVA Press.
View | Download (ext.)
 
[5]
2017 | Conference Paper | IST-REx-ID: 1000   OA
Kolesnikov A, Lampert C. PixelCNN models with auxiliary variables for natural image modeling. In: Vol 70. Omnipress; 2017:1905-1914.
View | Download (ext.)
 
[4]
2017 | Conference Paper | IST-REx-ID: 998   OA
Rebuffi SA, Kolesnikov A, Sperl G, Lampert C. iCaRL: Incremental classifier and representation learning. In: Vol 2017. IEEE; 2017:5533-5542. doi:10.1109/CVPR.2017.587
View | DOI | Download (ext.)
 
[3]
2016 | Conference Paper | IST-REx-ID: 1369   OA
Kolesnikov A, Lampert C. Seed, expand and constrain: Three principles for weakly-supervised image segmentation. In: Vol 9908. Springer; 2016:695-711. doi:10.1007/978-3-319-46493-0_42
View | DOI | Download (ext.)
 
[2]
2016 | Conference Paper | IST-REx-ID: 1102   OA
Kolesnikov A, Lampert C. Improving weakly-supervised object localization by micro-annotation. In: Proceedings of the British Machine Vision Conference 2016. Vol 2016-September. BMVA Press; 2016:92.1-92.12. doi:10.5244/C.30.92
View | DOI | Download (ext.)
 
[1]
2014 | Conference Paper | IST-REx-ID: 2171   OA
Kolesnikov A, Guillaumin M, Ferrari V, Lampert C. Closed-form approximate CRF training for scalable image segmentation. In: Fleet D, Pajdla T, Schiele B, Tuytelaars T, eds. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol 8691. Springer; 2014:550-565. doi:10.1007/978-3-319-10578-9_36
View | DOI | Download (ext.)
 

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Citation Style: AMA

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