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 4521–4530 of 4891 papers

TitleStatusHype
Fast PET reconstruction using Multi-scale Fully Convolutional Neural Networks—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
Fast Rigid Motion Segmentation via Incrementally-Complex Local Models—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
Fast Simulation of Particulate Suspensions Enabled by Graph Neural Network—0
Fast Stochastic MPC using Affine Disturbance Feedback Gains Learned Offline—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified