SOTAVerified

Computational Efficiency

Methods and optimizations to reduce the computational resources (e.g., time, memory, or power) needed for training and inference in models. This involves techniques that streamline processing, optimize algorithms, or leverage hardware to enhance performance without compromising accuracy.

Papers

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Showing 2841–2850 of 4891 papers

TitleStatusHype
Nonlinear subspace clustering by functional link neural networks—0
Unveiling Delay Effects in Traffic Forecasting: A Perspective from Spatial-Temporal Delay Differential Equations—0
A Robust Super-resolution Gridless Imaging Framework for UAV-borne SAR Tomography—0
kNN Algorithm for Conditional Mean and Variance Estimation with Automated Uncertainty Quantification and Variable Selection—0
Parallel Spiking Unit for Efficient Training of Spiking Neural Networks—0
Reimagining Reality: A Comprehensive Survey of Video Inpainting Techniques—0
Improving Global Weather and Ocean Wave Forecast with Large Artificial Intelligence Models—0
Data-Driven Filter Design in FBP: Transforming CT Reconstruction with Trainable Fourier SeriesCode0
EmoDM: A Diffusion Model for Evolutionary Multi-objective Optimization—0
Brain Tumor Diagnosis Using Quantum Convolutional Neural Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified