Kolesnikov, Alexander, Alina Kuznetsova, Christoph Lampert, and Vittorio Ferrari. “Detecting Visual Relationships Using Box Attention.”https://doi.org/10.1109/ICCVW.2019.00217__In Proceedings of the 2019 International Conference on Computer Vision Workshop. IEEE, 2019.https://doi.org/10.1109/ICCVW.2019.00217 .

Kolesnikov, Alexander. “Weakly-Supervised Segmentation and Unsupervised Modeling of Natural Images.”https://doi.org/10.15479/AT:ISTA:th_1021__Institute of Science and Technology Austria, 2018.https://doi.org/10.15479/AT:ISTA:th_1021 .

Ringbauer, Harald, Alexander Kolesnikov, David Field, and Nicholas H Barton. “Estimating Barriers to Gene Flow from Distorted Isolation-by-Distance Patterns.”https://doi.org/10.1534/genetics.117.300638__Genetics. Genetics Society of America, 2018.https://doi.org/10.1534/genetics.117.300638 .

Kolesnikov, Alexander, and Christoph Lampert. “PixelCNN Models with Auxiliary Variables for Natural Image Modeling.” In 34th International Conference on Machine Learning, 70:1905–14. JMLR, 2017.

Rebuffi, Sylvestre Alvise, Alexander Kolesnikov, Georg Sperl, and Christoph Lampert. “ICaRL: Incremental Classifier and Representation Learning,”https://doi.org/10.1109/CVPR.2017.587__2017:5533–42. IEEE, 2017.https://doi.org/10.1109/CVPR.2017.587 .

Royer, Amélie, Alexander Kolesnikov, and Christoph Lampert. “Probabilistic Image Colorization,”https://doi.org/10.5244/c.31.85__85.1-85.12. BMVA Press, 2017.https://doi.org/10.5244/c.31.85 .

Kolesnikov, Alexander, and Christoph Lampert. “Improving Weakly-Supervised Object Localization by Micro-Annotation.”https://doi.org/10.5244/C.30.92__In Proceedings of the British Machine Vision Conference 2016, 2016–September:92.1-92.12. BMVA Press, 2016.https://doi.org/10.5244/C.30.92 .

Kolesnikov, Alexander, and Christoph Lampert. “Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation,”https://doi.org/10.1007/978-3-319-46493-0_42__9908:695–711. Springer, 2016.https://doi.org/10.1007/978-3-319-46493-0_42 .

Kolesnikov, Alexander, Matthieu Guillaumin, Vittorio Ferrari, and Christoph Lampert. “Closed-Form Approximate CRF Training for Scalable Image Segmentation.”https://doi.org/10.1007/978-3-319-10578-9_36__In Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), edited by David Fleet, Tomas Pajdla, Bernt Schiele, and Tinne Tuytelaars, 8691:550–65. Springer, 2014.https://doi.org/10.1007/978-3-319-10578-9_36 .