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 3561–3570 of 4891 papers

TitleStatusHype
Defect Transformer: An Efficient Hybrid Transformer Architecture for Surface Defect Detection—0
Multiscale Causal Structure Learning—0
Action Recognition With Motion Diversification and Dynamic Selection—0
AdamNODEs: When Neural ODE Meets Adaptive Moment EstimationCode0
Safe Drone Flight with Time-Varying Backup Controllers—0
DeepSNR: A deep learning foundation for offline gravitational wave detection—0
Numerical Comparisons of Linear Power Flow Approximations: Optimality, Feasibility, and Computation Time—0
ATC-Based Scenario Decomposition Algorithm for Optimal Power Flow of Distribution Networks Considering High Photovoltaic Penetration—0
Style Interleaved Learning for Generalizable Person Re-identificationCode0
Online SuBmodular + SuPermodular (BP) Maximization with Bandit FeedbackCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified