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 631–640 of 4891 papers

TitleStatusHype
Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point CloudsCode1
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM ImagesCode1
Faith-Shap: The Faithful Shapley Interaction IndexCode1
Deep Learning for Hate Speech Detection: A Comparative StudyCode1
Guidelines and Evaluation of Clinical Explainable AI in Medical Image AnalysisCode1
Cross-Modality Multi-Atlas Segmentation via Deep Registration and Label FusionCode1
Event-based Video Reconstruction via Potential-assisted Spiking Neural NetworkCode1
On Evaluation Metrics for Graph Generative ModelsCode1
TSA-Net: Tube Self-Attention Network for Action Quality AssessmentCode1
S-Walk: Accurate and Scalable Session-based Recommendationwith Random WalksCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified