Imagen de Portada

A Probabilistic Approach to Learning the Degree of Equivariance in Steerable CNNs

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Veefkind, Lars, Cesa, Gabriele
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Adaptive Sampling for Continuous Group Equivariant Neural Networks
por: Inal, Berfin, et al.
Publicado: (2024)

Equivariant amortized inference of poses for cryo-EM
por: de Ruijter, Larissa, et al.
Publicado: (2024)

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing
por: Behboodi, Arash, et al.
Publicado: (2024)

Bases of Steerable Kernels for Equivariant CNNs: From 2D Rotations to the Lorentz Group
por: Garbarz, Alan
Publicado: (2026)

A Probabilistic Approach to Pose Synchronization for Multi-Reference Alignment with Applications to MIMO Wireless Communication Systems
por: Romijnders, Rob, et al.
Publicado: (2025)

Conditional Clifford-Steerable CNNs with Complete Kernel Basis for PDE Modeling
por: Szarvas, Bálint László, et al.
Publicado: (2025)

Neural Lattice Reduction: A Self-Supervised Geometric Deep Learning Approach
por: Marchetti, Giovanni Luca, et al.
Publicado: (2023)

Learning Probabilistic Symmetrization for Architecture Agnostic Equivariance
por: Kim, Jinwoo, et al.
Publicado: (2023)

Near-Optimal Regret for Distributed Adversarial Bandits: A Black-Box Approach
por: Qiu, Hao, et al.
Publicado: (2026)

Reliable Evaluation of Attribution Maps in CNNs: A Perturbation-Based Approach
por: Nieradzik, Lars, et al.
Publicado: (2024)

A Perturbation Approach to Unconstrained Linear Bandits
por: Jacobsen, Andrew, et al.
Publicado: (2026)

Graph-CNNs for RF Imaging: Learning the Electric Field Integral Equations
por: Stylianopoulos, Kyriakos, et al.
Publicado: (2025)

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

Multitask Online Learning: Listen to the Neighborhood Buzz
por: Achddou, Juliette, et al.
Publicado: (2023)

Learning Steerable Clarification Policies with Collaborative Self-play
por: Berant, Jonathan, et al.
Publicado: (2025)

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

On Universality Classes of Equivariant Networks
por: Pacini, Marco, et al.
Publicado: (2025)

Learning Policy Representations for Steerable Behavior Synthesis
por: Li, Beiming, et al.
Publicado: (2026)

Cooperative Online Learning with Feedback Graphs
por: Cesa-Bianchi, Nicolò, et al.
Publicado: (2021)

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

Gradient-Variation Regret Bounds for Unconstrained Online Learning
por: Zhao, Yuheng, et al.
Publicado: (2026)

Local Look-Ahead Guidance via Verifier-in-the-Loop for Automated Theorem Proving
por: Rajaee, Sara, et al.
Publicado: (2025)

Stable and Steerable Sparse Autoencoders with Weight Regularization
por: Jedryszek, Piotr, et al.
Publicado: (2026)

Equivariant Graph Network Approximations of High-Degree Polynomials for Force Field Prediction
por: Xu, Zhao, et al.
Publicado: (2024)

Bayesian Preference Learning for Test-Time Steerable Reward Models
por: Hong, Jiwoo, et al.
Publicado: (2026)

Separation Power of Equivariant Neural Networks
por: Pacini, Marco, et al.
Publicado: (2024)

Scalable Lipschitz Estimation for CNNs
por: Sulehman, Yusuf, et al.
Publicado: (2024)

Clifford-Steerable Convolutional Neural Networks
por: Zhdanov, Maksim, et al.
Publicado: (2024)

Steerable Neural ODEs on Homogeneous Spaces
por: Andersdotter, Emma, et al.
Publicado: (2026)

A Characterization Theorem for Equivariant Networks with Point-wise Activations
por: Pacini, Marco, et al.
Publicado: (2024)

Distributed Online Optimization with Stochastic Agent Availability
por: Achddou, Juliette, et al.
Publicado: (2024)

Sparsity-Agnostic Linear Bandits with Adaptive Adversaries
por: Jin, Tianyuan, et al.
Publicado: (2024)

Lookahead identification in adversarial bandits: accuracy and memory bounds
por: Brukhim, Nataly, et al.
Publicado: (2026)

Online Linear Regression with Paid Stochastic Features
por: Merlis, Nadav, et al.
Publicado: (2025)

Steerable but Not Decodable: Function Vectors Operate Beyond the Logit Lens
por: Nadaf, Mohammed Suhail B
Publicado: (2026)

EquiformerV2: Improved Equivariant Transformer for Scaling to Higher-Degree Representations
por: Liao, Yi-Lun, et al.
Publicado: (2023)

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

An Equivariance Toolbox for Learning Dynamics
por: Yang, Yongyi, et al.
Publicado: (2025)

Generative Molecular Design with Steerable and Granular Synthesizability Control
por: Guo, Jeff, et al.
Publicado: (2025)

ReQuestNet: A Foundational Learning model for Channel Estimation
por: Pratik, Kumar, et al.
Publicado: (2025)