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

Rebuffi, Sylvestre Alvise, et al. ICaRL: Incremental Classifier and Representation Learning. Vol. 2017, IEEE, 2017, pp. 5533–42, doi:10.1109/CVPR.2017.587.

Royer, Amélie, et al. Probabilistic Image Colorization. BMVA Press, 2017, p. 85.1-85.12, doi:10.5244/c.31.85.

Zimin, Alexander, and Christoph Lampert. Learning Theory for Conditional Risk Minimization. Vol. 54, ML Research Press, 2017, pp. 213–22.

Pentina, Anastasia, and Christoph Lampert. Multi-Task Learning with Labeled and Unlabeled Tasks. Vol. 70, ML Research Press, 2017, pp. 2807–16.

Pentina, Anastasia, and Ruth Urner. Lifelong Learning with Weighted Majority Votes. Vol. 29, Neural Information Processing Systems, 2016, pp. 3619–27.

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

Martius, Georg S., et al. Compliant Control for Soft Robots: Emergent Behavior of a Tendon Driven Anthropomorphic Arm. Vol. 2016–November, 7759138, IEEE, 2016, doi:10.1109/IROS.2016.7759138.

Kolesnikov, Alexander, and Christoph Lampert. Seed, Expand and Constrain: Three Principles for Weakly-Supervised Image Segmentation. Vol. 9908, Springer, 2016, pp. 695–711, doi:10.1007/978-3-319-46493-0_42.

Pielorz, Jasmin, and Christoph Lampert. Optimal Geospatial Allocation of Volunteers for Crisis Management. 7402041, IEEE, 2016, doi:10.1109/ICT-DM.2015.7402041.

Martius, Georg S., et al. “Self-Organized Control of an Tendon Driven Arm by Differential Extrinsic Plasticity.”10.7551/978-0-262-33936-0-ch029__Proceedings of the Artificial Life Conference 2016, vol. 28, MIT Press, 2016, pp. 142–43, doi:10.7551/978-0-262-33936-0-ch029.

Pentina, Anastasia. Theoretical Foundations of Multi-Task Lifelong Learning. Institute of Science and Technology Austria, 2016, doi:10.15479/AT:ISTA:TH_776.

Pentina, Anastasia, and Christoph Lampert. Lifelong Learning with Non-i.i.d. Tasks. Vol. 2015, Neural Information Processing Systems, 2015, pp. 1540–48.

Xia, Wei, et al. “Segmentation over Detection via Optimal Sparse Reconstructions.”10.1109/TCSVT.2014.2379972__IEEE Transactions on Circuits and Systems for Video Technology, vol. 25, no. 8, IEEE, 2015, pp. 1295–308, doi:10.1109/TCSVT.2014.2379972.

Der, Ralf, and Georg S. Martius. “Novel Plasticity Rule Can Explain the Development of Sensorimotor Intelligence.”10.1073/pnas.1508400112__PNAS, vol. 112, no. 45, National Academy of Sciences, 2015, pp. 24–32, doi:10.1073/pnas.1508400112.

Pentina, Anastasia, and Shai Ben David. Multi-Task and Lifelong Learning of Kernels. Vol. 9355, Springer, 2015, pp. 194–208, doi:10.1007/978-3-319-24486-0_13.

Shah, Neel, et al. A Multi-Plane Block-Coordinate Frank-Wolfe Algorithm for Training Structural SVMs with a Costly Max-Oracle. IEEE, 2015, pp. 2737–45, doi:10.1109/CVPR.2015.7298890.

Royer, Amélie, and Christoph Lampert. Classifier Adaptation at Prediction Time. IEEE, 2015, pp. 1401–09, doi:10.1109/CVPR.2015.7298746.

Lampert, Christoph. Predicting the Future Behavior of a Time-Varying Probability Distribution. IEEE, 2015, pp. 942–50, doi:10.1109/CVPR.2015.7298696.

Pentina, Anastasia, et al. Curriculum Learning of Multiple Tasks. IEEE, 2015, pp. 5492–500, doi:10.1109/CVPR.2015.7299188.