Zilverling

dr. E. Mocanu (Elena)

Universitair docent
EEMCS-CS-DMB
Zilverling
e.mocanu@utwente.nl
+31534898596
Visitekaartje

Expertises

  • Computer Science

    • Deep Learning Method
    • Restricted Boltzmann Machine
    • Neural Network
    • Deep Reinforcement Learning
    • Smart Grid
    • Reinforcement Learning
    • Feature Extraction
    • Deep Neural Network

Organisaties

Publicaties

2025

Addressing the Collaboration Dilemma in Low-Data Federated Learning via Transient Sparsity (2025)[Working paper › Preprint]. ArXiv.org. Xiao, Q., Wu, B., Poddubnyy, A., Mocanu, E., Nguyen, P. H., Pechenizkiy, M. & Mocanu, D. C.https://doi.org/10.48550/arXiv.2506.00932NeuroTrails: Training with Dynamic Sparse Heads as the Key to Effective Ensembling (2025)[Working paper › Preprint]. ArXiv.org. Grooten, B., Hasanov, F., Zhang, C., Xiao, Q., Wu, B., Atashgahi, Z., Sokar, G., Liu, S., Yin, L., Mocanu, E., Pechenizkiy, M. & Mocanu, D. C.https://doi.org/10.48550/arXiv.2505.17909Grassmannian Low-Rank Representation for Efficient Training of Deep Neural Networks (2025)[Contribution to conference › Poster] Netherlands Conference on Computer Vision, NCCV 2025. Pasande, M., Mocanu, E. & van Keulen, M.Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness (2025)In 13th International Conference on Learning Representations, ICLR 2025 (pp. 28220-28246). Wu, B., Xiao, Q., Wang, S., Strisciuglio, N., Pechenizkiy, M., Keulen, M. v., Mocanu, D. C. & Mocanu, E.https://openreview.net/forum?id=daUQ7vmGap

2024

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation (2024)In NIPS '24: Proceedings of the 38th International Conference on Neural Information Processing Systems (pp. 118483-118512). Article 3762 (Advances in Neural Information Processing Systems; Vol. 37) (E-pub ahead of print/First online). Wu, B., Xiao, Q., Liu, S., Yin, L., Pechenizkiy, M., Mocanu, D. C., van Keulen, M. & Mocanu, E.https://doi.org/10.5555/3737916.3741678Dynamic Sparse Training versus Dense Training: The Unexpected Winner in Image Corruption Robustness (2024)[Working paper › Preprint]. ArXiv.org. Wu, B., Xiao, Q., Wang, S., Strisciuglio, N., Pechenizkiy, M., van Keulen, M., Mocanu, D. C. & Mocanu, E.https://doi.org/10.48550/arXiv.2410.03030Insights into Dynamic Sparse Training: Theory Meets Practice (2024)[Contribution to conference › Poster] European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2024. Wu, B., van Keulen, M., Mocanu, D. C. & Mocanu, E.Digital Twin-Empowered Autonomous Driving for E-mobility: Concept, framework, and modeling (2024)IEEE Electrification Magazine, 12(3), 68-77. Li, Y., Xu, J., Li, T., Mocanu, E., Jensen, C. S., Gao, D. W. & Zhang, Y.https://doi.org/10.1109/MELE.2024.3423148E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation (2024)In 38th Annual Conference on Neural Information Processing Systems, NeurIPS 2024. MLResearchPress. Wu, B., Xiao, Q., Liu, S., Yin, L., Pechenizkiy, M., Mocanu, D. C., van Keulen, M. & Mocanu, E.https://openreview.net/forum?id=Xp8qhdmeb4

2023

E2ENet: Dynamic Sparse Feature Fusion for Accurate and Efficient 3D Medical Image Segmentation (2023)[Working paper › Preprint]. ArXiv.org. Wu, B., Xiao, Q., Liu, S., Yin, L., Pechenizkiy, M., Mocanu, D. C., van Keulen, M. & Mocanu, E.https://doi.org/10.48550/arXiv.2312.04727

Onderzoeksprofielen

Vakken collegejaar 2026/2027

Vakken in het huidig collegejaar worden toegevoegd op het moment dat zij definitief zijn in het Osiris systeem. Daarom kan het zijn dat de lijst nog niet compleet is voor het gehele collegejaar.

Vakken collegejaar 2025/2026

Vakken collegejaar 2024/2025

QR codeScan de QR-code of
Download vCard