Imagen de Portada

Rotary Position Encodings for Graphs

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autores principales:	Reid, Isaac, Sehanobish, Arijit, Höfs, Cederik, Mlodozeniec, Bruno, Vulpius, Leonhard, Barbero, Federico, Weller, Adrian, Choromanski, Krzysztof, Turner, Richard E., Veličković, Petar
Formato:	Preprint
Publicado:	2025
Materias:	Machine Learning Artificial Intelligence
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Computationally-efficient Graph Modeling with Refined Graph Random Features
por: Choromanski, Krzysztof, et al.
Publicado: (2025)

Optimal Time Complexity Algorithms for Computing General Random Walk Graph Kernels on Sparse Graphs
por: Choromanski, Krzysztof, et al.
Publicado: (2024)

Round and Round We Go! What makes Rotary Positional Encodings useful?
por: Barbero, Federico, et al.
Publicado: (2024)

RelFlexformer: Efficient Attention 3D-Transformers for Integrable Relative Positional Encodings
por: Kim, Byeongchan, et al.
Publicado: (2026)

General Graph Random Features
por: Reid, Isaac, et al.
Publicado: (2023)

Variance-Reducing Couplings for Random Features
por: Reid, Isaac, et al.
Publicado: (2024)

Graph Random Features for Scalable Gaussian Processes
por: Zhang, Matthew, et al.
Publicado: (2025)

SWING: Unlocking Implicit Graph Representations for Graph Random Features
por: Manenti, Alessandro, et al.
Publicado: (2026)

Repelling Random Walks
por: Reid, Isaac, et al.
Publicado: (2023)

Statistical Reconstruction For Anisotropic X-ray Dark-Field Tomography
por: Frank, David, et al.
Publicado: (2025)

Scalable Neural Network Kernels
por: Sehanobish, Arijit, et al.
Publicado: (2023)

Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning
por: Chowdhury, Somnath Basu Roy, et al.
Publicado: (2024)

Softmax is not Enough (for Sharp Size Generalisation)
por: Veličković, Petar, et al.
Publicado: (2024)

Probabilistic Modelling is Sufficient for Causal Inference
por: Mlodozeniec, Bruno, et al.
Publicado: (2025)

Distributional Training Data Attribution: What do Influence Functions Sample?
por: Mlodozeniec, Bruno, et al.
Publicado: (2025)

Fast Tree-Field Integrators: From Low Displacement Rank to Topological Transformers
por: Choromanski, Krzysztof, et al.
Publicado: (2024)

Structured Unrestricted-Rank Matrices for Parameter Efficient Fine-tuning
por: Sehanobish, Arijit, et al.
Publicado: (2024)

Not How Many, But Which: Parameter Placement in Low-Rank Adaptation
por: Sehanobish, Arijit, et al.
Publicado: (2026)

Leveraging Classical Algorithms for Graph Neural Networks
por: Wu, Jason, et al.
Publicado: (2025)

Perplexity Cannot Always Tell Right from Wrong
por: Veličković, Petar, et al.
Publicado: (2026)

Learning a Fourier Transform for Linear Relative Positional Encodings in Transformers
por: Choromanski, Krzysztof Marcin, et al.
Publicado: (2023)

Better Hessians Matter: Studying the Impact of Curvature Approximations in Influence Functions
por: Hong, Steve, et al.
Publicado: (2025)

Cross-device Zero-shot Label Transfer via Alignment of Time Series Foundation Model Embeddings
por: Ravindra, Neal G., et al.
Publicado: (2025)

Linear Transformer Topological Masking with Graph Random Features
por: Reid, Isaac, et al.
Publicado: (2024)

Commute-Time-Optimised Graphs for GNNs
por: Sterner, Igor, et al.
Publicado: (2024)

How do LLMs Compute Verbal Confidence
por: Kumaran, Dharshan, et al.
Publicado: (2026)

Cayley Graph Propagation
por: Wilson, JJ, et al.
Publicado: (2024)

Incremental Transformer Neural Processes
por: Mortimer, Philip, et al.
Publicado: (2026)

Recurrent Aggregators in Neural Algorithmic Reasoning
por: Xu, Kaijia, et al.
Publicado: (2024)

Temporal Graph Rewiring with Expander Graphs
por: Petrović, Katarina, et al.
Publicado: (2024)

Why do LLMs attend to the first token?
por: Barbero, Federico, et al.
Publicado: (2025)

O BARCO VAI SE LEVANDORETRATO DE UMA IMIGRANTE BRASILEIRA EM PARAMA-RIBO, SURINAME
por: Carolina Carret Höfs
Publicado: (2007)

Influence Functions for Scalable Data Attribution in Diffusion Models
por: Mlodozeniec, Bruno, et al.
Publicado: (2024)

EUGens: Efficient, Unified, and General Dense Layers
por: Kim, Sang Min, et al.
Publicado: (2024)

EUGens: Efficient, Unified, and General Dense Layers
por: Kim, Sang Min, et al.
Publicado: (2026)

Near-Linear Time Generalized Sinkhorn Algorithms for Bounded Genus Graphs
por: Choromanski, Krzysztof, et al.
Publicado: (2026)

Head-wise Adaptive Rotary Positional Encoding for Fine-Grained Image Generation
por: Li, Jiaye, et al.
Publicado: (2025)

Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
por: Gavranović, Bruno, et al.
Publicado: (2024)

Parallel Algorithms Align with Neural Execution
por: Engelmayer, Valerie, et al.
Publicado: (2023)

Positional Attention: Expressivity and Learnability of Algorithmic Computation
por: de Luca, Artur Back, et al.
Publicado: (2024)