:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Berndt, Torben, Walker, Benjamin, Qin, Tiexin, Stühmer, Jan, Kormilitzin, Andrey
Format:	Preprint
Published:	2025
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2506.20324
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Approximate Equivariance via Projection-based Regularisation
by: Berndt, Torben, et al.
Published: (2026)

Universal Time Series Generation with Neural Controlled Differential Equations
by: Berndt, Torben, et al.
Published: (2026)

Learning Dynamic Graph Embeddings with Neural Controlled Differential Equations
by: Qin, Tiexin, et al.
Published: (2023)

Log Neural Controlled Differential Equations: The Lie Brackets Make a Difference
by: Walker, Benjamin, et al.
Published: (2024)

Set-LLM: A Permutation-Invariant LLM
by: Egressy, Beni, et al.
Published: (2025)

A Primer on the Signature Method in Machine Learning
by: Chevyrev, Ilya, et al.
Published: (2016)

Graph Neural Networks and Spatial Information Learning for Post-Processing Ensemble Weather Forecasts
by: Feik, Moritz, et al.
Published: (2024)

Generalizing to New Dynamical Systems via Frequency Domain Adaptation
by: Qin, Tiexin, et al.
Published: (2025)

Graph Neural Networks for Learning Equivariant Representations of Neural Networks
by: Kofinas, Miltiadis, et al.
Published: (2024)

Permutation Equivariant Neural Networks for Symmetric Tensors
by: Pearce-Crump, Edward
Published: (2025)

A Two-Parameter Weibull Framework for Diagnosing Transformer Weight Distributions
by: Ding, Tiexin
Published: (2026)

Theoretical Guarantees for Permutation-Equivariant Quantum Neural Networks
by: Schatzki, Louis, et al.
Published: (2022)

Revisiting Multi-Permutation Equivariance through the Lens of Irreducible Representations
by: Sverdlov, Yonatan, et al.
Published: (2024)

HAMLET: Graph Transformer Neural Operator for Partial Differential Equations
by: Bryutkin, Andrey, et al.
Published: (2024)

Connecting Permutation Equivariant Neural Networks and Partition Diagrams
by: Pearce-Crump, Edward
Published: (2022)

Grappa -- A Machine Learned Molecular Mechanics Force Field
by: Seute, Leif, et al.
Published: (2024)

Solving Partial Differential Equations with Equivariant Extreme Learning Machines
by: Harder, Hans, et al.
Published: (2024)

Continuously Evolving Graph Neural Controlled Differential Equations for Traffic Forecasting
by: Wu, Jiajia, et al.
Published: (2024)

DuSEGO: Dual Second-order Equivariant Graph Ordinary Differential Equation
by: Wang, Yingxu, et al.
Published: (2024)

Geometry of Linear Neural Networks: Equivariance and Invariance under Permutation Groups
by: Kohn, Kathlén, et al.
Published: (2023)

Concept Prerequisite Relation Prediction by Using Permutation-Equivariant Directed Graph Neural Networks
by: Qu, Xiran, et al.
Published: (2023)

Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?
by: Cen, Jiacheng, et al.
Published: (2024)

Harnessing Equivariance: Modeling Turbulence with Graph Neural Networks
by: Kurz, Marius, et al.
Published: (2025)

Projected Neural Differential Equations for Learning Constrained Dynamics
by: White, Alistair, et al.
Published: (2024)

Morphological-Symmetry-Equivariant Heterogeneous Graph Neural Network for Robotic Dynamics Learning
by: Xie, Fengze, et al.
Published: (2024)

Learning Neural Differential Algebraic Equations via Operator Splitting
by: Koch, James, et al.
Published: (2024)

On the Expressive Power of Permutation-Equivariant Weight-Space Networks
by: Dayan, Adir, et al.
Published: (2026)

Relaxing Continuous Constraints of Equivariant Graph Neural Networks for Physical Dynamics Learning
by: Zheng, Zinan, et al.
Published: (2024)

Control and optimization for Neural Partial Differential Equations in Supervised Learning
by: Bensoussan, Alain, et al.
Published: (2025)

Permutation Equivariant Model-based Offline Reinforcement Learning for Auto-bidding
by: Mou, Zhiyu, et al.
Published: (2025)

Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints
by: White, Alistair, et al.
Published: (2023)

Relaxed Equivariant Graph Neural Networks
by: Hofgard, Elyssa, et al.
Published: (2024)

Neural Fourier Transform: A General Approach to Equivariant Representation Learning
by: Koyama, Masanori, et al.
Published: (2023)

Graph Pseudotime Analysis and Neural Stochastic Differential Equations for Analyzing Retinal Degeneration Dynamics and Beyond
by: Shi, Dai, et al.
Published: (2025)

Neural Controlled Differential Equations with Quantum Hidden Evolutions
by: Yang, Lingyi, et al.
Published: (2024)

On the Generalization and Approximation Capacities of Neural Controlled Differential Equations
by: Bleistein, Linus, et al.
Published: (2023)

Bridging Dynamic Factor Models and Neural Controlled Differential Equations for Nowcasting GDP
by: Lim, Seonkyu, et al.
Published: (2024)

Equivariant Neural Tangent Kernels
by: Misof, Philipp, et al.
Published: (2024)

On The Temporal Domain of Differential Equation Inspired Graph Neural Networks
by: Eliasof, Moshe, et al.
Published: (2024)

Disentangled Representation Learning for Parametric Partial Differential Equations
by: Liu, Ning, et al.
Published: (2024)