Nicki Skafte Detlefsen

PhD Student, Department of Applied Mathematics and Computer Science
Cognitive Systems

Phone55227
Emailnsde@dtu.dk
Websitehttp://www.compute.dtu.dk

Richard Petersens Plads, 321, 006
2800 Kgs. Lyngby
Denmark

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4 Article in proceedings

Diffeomorphic Temporal Alignment Nets
Weber, R. S., Eyal, M., Detlefsen, N. S., Shriki, O. & Freifeld, O., 2019, Advances in Neural Information Processing Systems 32 . Neural Information Processing Systems Foundation, 12 p. 8884. (Advances in Neural Information Processing Systems, Vol. 32).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Open Access
File
10 Downloads (Pure)
Explicit Disentanglement of Appearance and Perspective in Generative Models
Detlefsen, N. S. & Hauberg, S., 2019, Proceedings of 33rd Conference on Neural Information Processing Systems. 19 p.
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

File

42 Downloads (Pure)
Reliable training and estimation of variance networks
Detlefsen, N. S., Jørgensen, M. & Hauberg, S., 2019, Proceedings of 33rd Conference on Neural Information Processing Systems. 19 p.
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

File
41 Downloads (Pure)
Deep Diffeomorphic Transformer Networks
Detlefsen, N. S., Freifeld, O. & Hauberg, S., 2018, Proceedings of 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition. IEEE, p. 4403-4412 (I E E E Conference on Computer Vision and Pattern Recognition. Proceedings).
Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Open Access
File
8 Downloads (Pure)

1 Active

Deep Metric Learning
Detlefsen, N. S., Hauberg, S., Winther, O., Alstrøm, T. S., Ferkinghoff-Borg, J. & Rainforth, T.
Fonde
01/09/2017 → 01/12/2020
Project: PhD

Diffeomorphic Temporal Alignment Nets

Explicit Disentanglement of Appearance and Perspective in Generative Models

Reliable training and estimation of variance networks

Deep Diffeomorphic Transformer Networks

Deep Metric Learning