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Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning
Published in NeurIPS, 2025
Permutation equivariant Neural Graph CDEs for efficient dynamic graph representation learning.
Recommended citation: Torben Berndt, Benjamin Walker, Tiexin Qin, Jan Stühmer and Andrey Kormilitzin. (2025). "Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning." arXiv:2506.20324.
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Approximate Equivariance via Projection-based Regularisation
Published in ICML, 2026
A projection-based regulariser for approximate equivariance that penalises non-equivariance at the operator level.
Recommended citation: Torben Berndt and Jan Stühmer. (2026). "Approximate equivariance via projection-based regularisation." arXiv:2601.05028.
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Universal Time Series Generation with Neural Controlled Differential Equations
Published in arXiv, 2026
Generative SLiCEs extend maximally expressive continuous-time state space models to flow matching on path space for probabilistic time-series forecasting.
Recommended citation: Torben Berndt*, Elyes Farjallah*, Leif Seute, Raeid Saqur, Benjamin Walker† and Jan Stühmer†. (2026). "Universal Time Series Generation with Neural Controlled Differential Equations." arXiv preprint.
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