Spatial Interpolation
15 papers with code • 0 benchmarks • 0 datasets
Benchmarks
These leaderboards are used to track progress in Spatial Interpolation
Latest papers
AID: Attention Interpolation of Text-to-Image Diffusion
qy-h00/attention-interpolation-diffusion
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To that end, we introduce a novel training-free technique named Attention Interpolation via Diffusion (AID).
NIIRF: Neural IIR Filter Field for HRTF Upsampling and Personalization
merlresearch/neural-iir-field
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Existing NF-based methods focused on estimating the magnitude of the HRTF from a given sound source direction, and the magnitude is converted to a finite impulse response (FIR) filter.
SSIN: Self-Supervised Learning for Rainfall Spatial Interpolation
jlidw/ssin
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Inspired by the Cloze task and BERT, we fully consider the characteristics of spatial interpolation and design the SpaFormer model based on the Transformer architecture as the core of SSIN.
Kriging Convolutional Networks
Spatial interpolation is a class of estimation problems where locations with known values are used to estimate values at other locations, with an emphasis on harnessing spatial locality and trends.
Positive definite nonparametric regression using an evolutionary algorithm with application to covariance function estimation
We also extend our method to estimate covariance functions for point-referenced data.
Deep Spatial Domain Generalization
dyu62/deep-domain-generalization
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Spatial domain generalization is a spatial extension of domain generalization, which can generalize to unseen spatial domains in continuous 2D space.
Video Shadow Detection via Spatio-Temporal Interpolation Consistency Training
Our proposed approach is extensively validated on the ViSha dataset and a self-annotated dataset.
Intelligent Spatial Interpolation-based Frost Prediction Methodology using Artificial Neural Networks with Limited Local Data
In this article, a frost prediction method based on spatial interpolation is proposed.
Positional Encoder Graph Neural Networks for Geographic Data
Graph neural networks (GNNs) provide a powerful and scalable solution for modeling continuous spatial data.
Attention-Based Spatial Interpolation for House Price Prediction
darniton/ASI
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International Conference on Advances in Geographic Information Systems 2021
For that, we propose a hybrid attention mechanism that weights neighbors based on their similarity to the house in terms of structural features and geographic location.
