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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1871–1880 of 4891 papers

TitleStatusHype
Fast PET reconstruction using Multi-scale Fully Convolutional Neural Networks—0
FakeWatch ElectionShield: A Benchmarking Framework to Detect Fake News for Credible US Elections—0
Fast-Powerformer: A Memory-Efficient Transformer for Accurate Mid-Term Wind Power Forecasting—0
Fast Quasi-Optimal Power Flow of Flexible DC Traction Power Systems—0
FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection—0
Fast Ridge Regression with Randomized Principal Component Analysis and Gradient Descent—0
FakeWatch: A Framework for Detecting Fake News to Ensure Credible Elections—0
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks—0
Fast Screening Algorithm for Rotation and Scale Invariant Template Matching—0
Coil Sketching for computationally-efficient MR iterative reconstruction—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified