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Found 6 papers, 1 papers with code
GWRBoost:A geographically weighted gradient boosting method for explainable quantification of spatially-varying relationships
The geographically weighted regression (GWR) is an essential tool for estimating the spatial variation of relationships between dependent and independent variables in geographical contexts.
Learning Branching Heuristics from Graph Neural Networks
From the GNN model, we introduce an approach to learn a branching heuristic for combinatorial optimization problems.
Code Representation Learning with Prüfer Sequences
In this paper, we propose to use the Pr\"ufer sequence of the Abstract Syntax Tree (AST) of a computer program to design a sequential representation scheme that preserves the structural information in an AST.
Content Filtering Enriched GNN Framework for News Recommendation
It is compatible with existing GNN-based approaches for news recommendation and can capture both collaborative and content filtering information simultaneously.
ScaleFreeCTR: MixCache-based Distributed Training System for CTR Models with Huge Embedding Table
Different from the models with dense training data, the training data for CTR models is usually high-dimensional and sparse.
Precessions of Spheroidal Stars under Lorentz Violation and Observational Consequences
The Standard-Model Extension (SME) is an effective-field-theoretic framework that catalogs all Lorentz-violating field operators.
General Relativity and Quantum Cosmology High Energy Astrophysical Phenomena High Energy Physics - Phenomenology
