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 501–510 of 4891 papers

TitleStatusHype
Multiscale Context-Aware Ensemble Deep KELM for Efficient Hyperspectral Image ClassificationCode1
Multi-scale Matching Networks for Semantic CorrespondenceCode1
DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable ConvolutionCode1
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelsCode1
Enhancing Vision-Language Few-Shot Adaptation with Negative LearningCode1
NeRF and Gaussian Splatting SLAM in the WildCode1
A Transformer-based Framework for Multivariate Time Series Representation LearningCode1
Neural incomplete factorization: learning preconditioners for the conjugate gradient methodCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Deep Speech Synthesis from MRI-Based Articulatory RepresentationsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified