Cover Image

Approximate Equivariance via Projection-based Regularisation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Berndt, Torben, Stühmer, Jan
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Permutation Equivariant Neural Controlled Differential Equations for Dynamic Graph Representation Learning
by: Berndt, Torben, et al.
Published: (2025)

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

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

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

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

Approximately Equivariant Neural Processes
by: Ashman, Matthew, et al.
Published: (2024)

Approximate Equivariance in Reinforcement Learning
by: Park, Jung Yeon, et al.
Published: (2024)

Learning (Approximately) Equivariant Networks via Constrained Optimization
by: Manolache, Andrei, et al.
Published: (2025)

Approximation-Generalization Trade-offs under (Approximate) Group Equivariance
by: Petrache, Mircea, et al.
Published: (2023)

Generating Highly Designable Proteins with Geometric Algebra Flow Matching
by: Wagner, Simon, et al.
Published: (2024)

Learning conformational ensembles of proteins based on backbone geometry
by: Wolf, Nicolas, et al.
Published: (2025)

Enhanced Feature Learning via Regularisation: Integrating Neural Networks and Kernel Methods
by: Follain, Bertille, et al.
Published: (2024)

Monte Carlo Functional Regularisation for Continual Learning
by: Hao, Pengcheng, et al.
Published: (2025)

On Self-Supervised Dynamic Incremental Regularised Adaptation
by: Ghobrial, Abanoub, et al.
Published: (2023)

Regularising NARX models with multi-task learning
by: Bee, Sarah, et al.
Published: (2025)

Temporal Smoothness Regularisers for Neural Link Predictors
by: Dileo, Manuel, et al.
Published: (2023)

DIRA: Dynamic Domain Incremental Regularised Adaptation
by: Ghobrial, Abanoub, et al.
Published: (2022)

Resource-Constrained Affect Modelling via Variance Regularisation Pruning
by: Pinitas, Kosmas, et al.
Published: (2026)

Algebraic Priors for Approximately Equivariant Networks
by: Ali, Riccardo, et al.
Published: (2025)

Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry
by: Sannai, Akiyoshi, et al.
Published: (2024)

Canonical Regularisation of Wide Feature-Learning Neural Networks
by: Whittle, George, et al.
Published: (2026)

Function-Space Empirical Bayes Regularisation with Student's t Priors
by: Hao, Pengcheng, et al.
Published: (2026)

Evidence on the Regularisation Properties of Maximum-Entropy Reinforcement Learning
by: Hosseinkhan-Boucher, Rémy, et al.
Published: (2025)

Symmetry-Based Structured Matrices for Efficient Approximately Equivariant Networks
by: Samudre, Ashwin, et al.
Published: (2024)

Emergent Equivariance in Deep Ensembles
by: Gerken, Jan E., et al.
Published: (2024)

TASER: Task-Aware Stein Regularisation for Geometry-Driven Robustness
by: Kozyra, Michał, et al.
Published: (2026)

Stochastic Kernel Regularisation Improves Generalisation in Deep Kernel Machines
by: Milsom, Edward, et al.
Published: (2024)

Sobolev Space Regularised Pre Density Models
by: Kozdoba, Mark, et al.
Published: (2023)

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

Bootstrapping-based Regularisation for Reducing Individual Prediction Instability in Clinical Risk Prediction Models
by: Matijevic, Sara, et al.
Published: (2026)

Neural Collapse Dynamics: Depth, Activation, Regularisation, and Feature Norm Threshold
by: Rupa, Anamika Paul
Published: (2026)

An Infinite-Width Analysis on the Jacobian-Regularised Training of a Neural Network
by: Kim, Taeyoung, et al.
Published: (2023)

A Novel Approach to Regularising 1NN classifier for Improved Generalization
by: Challa, Aditya, et al.
Published: (2024)

DRED: Zero-Shot Transfer in Reinforcement Learning via Data-Regularised Environment Design
by: Garcin, Samuel, et al.
Published: (2024)

A Computable Measure of Suboptimality for Entropy-Regularised Variational Objectives
by: Chazal, Clémentine, et al.
Published: (2025)

Approximated Behavioral Metric-based State Projection for Federated Reinforcement Learning
by: Guo, Zengxia, et al.
Published: (2025)

Flexibility-Conditioned Protein Structure Design with Flow Matching
by: Viliuga, Vsevolod, et al.
Published: (2025)

Open-Set Graph Anomaly Detection via Normal Structure Regularisation
by: Wang, Qizhou, et al.
Published: (2023)

Consistency Regularised Gradient Flows for Inverse Problems
by: Spagnoletti, Alessio, et al.
Published: (2026)

Relaxed Equivariance via Multitask Learning
by: Elhag, Ahmed A., et al.
Published: (2024)