Copertina

Decomposition of Equivariant Maps via Invariant Maps: Application to Universal Approximation under Symmetry

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Sannai, Akiyoshi, Takai, Yuuki, Cordonnier, Matthieu
Natura:	Preprint
Pubblicazione:	2024
Soggetti:	Machine Learning
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE
di: Hashimoto, Koji, et al.
Pubblicazione: (2024)

Prover Agent: An Agent-Based Framework for Formal Mathematical Proofs
di: Baba, Kaito, et al.
Pubblicazione: (2025)

Universally Invariant Learning in Equivariant GNNs
di: Cen, Jiacheng, et al.
Pubblicazione: (2025)

Discovering New Theorems via LLMs with In-Context Proof Learning in Lean
di: Kasaura, Kazumi, et al.
Pubblicazione: (2025)

Convergence of Message Passing Graph Neural Networks with Generic Aggregation On Large Random Graphs
di: Cordonnier, Matthieu, et al.
Pubblicazione: (2023)

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

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

On Sampling with Approximate Transport Maps
di: Grenioux, Louis, et al.
Pubblicazione: (2023)

Integrating Large Language Models in Causal Discovery: A Statistical Causal Approach
di: Takayama, Masayuki, et al.
Pubblicazione: (2024)

Any-Subgroup Equivariant Networks via Symmetry Breaking
di: Goel, Abhinav, et al.
Pubblicazione: (2026)

Equivariant Latent Alignment via Flow Matching under Group Symmetries
di: Kim, Sunghyun, et al.
Pubblicazione: (2026)

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

Mapping Uncharted Symmetries: Machine Discovery in Combinatorics
di: Cainelli, Eugenio, et al.
Pubblicazione: (2026)

Equivariant Map and Agent Geometry for Autonomous Driving Motion Prediction
di: Wang, Yuping, et al.
Pubblicazione: (2023)

Equivariance via Minimal Frame Averaging for More Symmetries and Efficiency
di: Lin, Yuchao, et al.
Pubblicazione: (2024)

Beyond Mapping : Domain-Invariant Representations via Spectral Embedding of Optimal Transport Plans
di: Saoud, Abdel Djalil Sad, et al.
Pubblicazione: (2026)

A Policy Gradient Primal-Dual Algorithm for Constrained MDPs with Uniform PAC Guarantees
di: Kitamura, Toshinori, et al.
Pubblicazione: (2024)

Vocabulary for Universal Approximation: A Linguistic Perspective of Mapping Compositions
di: Cai, Yongqiang
Pubblicazione: (2023)

A Canonicalization Perspective on Invariant and Equivariant Learning
di: Ma, George, et al.
Pubblicazione: (2024)

Unsupervised Learning of Group Invariant and Equivariant Representations
di: Winter, Robin, et al.
Pubblicazione: (2022)

Symmetry Breaking and Equivariant Neural Networks
di: Kaba, Sékou-Oumar, et al.
Pubblicazione: (2023)

Equivariant Ensembles and Regularization for Reinforcement Learning in Map-based Path Planning
di: Theile, Mirco, et al.
Pubblicazione: (2024)

Approximately Equivariant Neural Processes
di: Ashman, Matthew, et al.
Pubblicazione: (2024)

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

Physics-Aligned Canonical Equivariant Fourier Neural Operator under Symmetry-Induced Shifts
di: Xu, Jiaxiao, et al.
Pubblicazione: (2026)

Equivariant Symmetry Breaking Sets
di: Xie, YuQing, et al.
Pubblicazione: (2024)

Lean Atlas: An Integrated Proof Environment for Scalable Human-AI Collaborative Formalization
di: Yanahama, Banri, et al.
Pubblicazione: (2026)

SPECA: Specification-to-Checklist Agentic Auditing for Multi-Implementation Systems -- A Case Study on Ethereum Clients
di: Kamba, Masato, et al.
Pubblicazione: (2026)

Lie Group Decompositions for Equivariant Neural Networks
di: Mironenco, Mircea, et al.
Pubblicazione: (2023)

Improving Equivariant Networks with Probabilistic Symmetry Breaking
di: Lawrence, Hannah, et al.
Pubblicazione: (2025)

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

Approximately Equivariant Quantum Neural Network for $p4m$ Group Symmetries in Images
di: Chang, Su Yeon, et al.
Pubblicazione: (2023)

Equivariant Manifold Neural ODEs and Differential Invariants
di: Andersdotter, Emma, et al.
Pubblicazione: (2024)

Invariant Subspace Decomposition
di: Lazzaretto, Margherita, et al.
Pubblicazione: (2024)

Categorical Equivariant Deep Learning: Category-Equivariant Neural Networks and Universal Approximation Theorems
di: Maruyama, Yoshihiro
Pubblicazione: (2025)

Gaussian Match-and-Copy: A Minimalist Benchmark for Studying Transformer Induction
di: Gonon, Antoine, et al.
Pubblicazione: (2026)

SWIFT: Mapping Sub-series with Wavelet Decomposition Improves Time Series Forecasting
di: Xie, Wenxuan, et al.
Pubblicazione: (2025)

Gauge-Equivariant Intrinsic Neural Operators for Geometry-Consistent Learning of Elliptic PDE Maps
di: Cheng, Pengcheng
Pubblicazione: (2026)

Learning Dynamics in RL Post-Training for Language Models
di: Tomihari, Akiyoshi
Pubblicazione: (2026)

A Materials Foundation Model via Hybrid Invariant-Equivariant Architectures
di: Yan, Keqiang, et al.
Pubblicazione: (2025)