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 2741–2750 of 4891 papers

TitleStatusHype
The Role of Extended Horizon Methodology in Renewable-Dense Grids With Inter-Day Long-Duration Energy Storage—0
The Power of Few: Accelerating and Enhancing Data Reweighting with Coreset Selection—0
Exploring Tokenization Strategies and Vocabulary Sizes for Enhanced Arabic Language ModelsCode0
A lightweight deep learning pipeline with DRDA-Net and MobileNet for breast cancer classification—0
Machine learning-based system reliability analysis with Gaussian Process Regression—0
EfficientMorph: Parameter-Efficient Transformer-Based Architecture for 3D Image RegistrationCode0
Hierarchical Provision of Distribution Grid Flexibility with Online Feedback Optimization—0
MEDPNet: Achieving High-Precision Adaptive Registration for Complex Die Castings—0
Mitigating Data Consistency Induced Discrepancy in Cascaded Diffusion Models for Sparse-view CT Reconstruction—0
Efficient Convolutional Forward Modeling and Sparse Coding in Multichannel Imaging—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified