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 881–890 of 4891 papers

TitleStatusHype
Implicit Generative Prior for Bayesian Neural NetworksCode0
ICE-BA: Incremental, Consistent and Efficient Bundle Adjustment for Visual-Inertial SLAMCode0
ICLabel: An automated electroencephalographic independent component classifier, dataset, and websiteCode0
A class of modular and flexible covariate-based covariance functions for nonstationary spatial modelingCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Cluster-Driven Expert Pruning for Mixture-of-Experts Large Language ModelsCode0
CloudFixer: Test-Time Adaptation for 3D Point Clouds via Diffusion-Guided Geometric TransformationCode0
CMML: Contextual Modulation Meta Learning for Cold-Start RecommendationCode0
CNNtention: Can CNNs do better with Attention?Code0
An Interpretable and Efficient Sleep Staging Algorithm: DetectsleepNetCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified