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 2841–2850 of 4891 papers

TitleStatusHype
ST-MLP: A Cascaded Spatio-Temporal Linear Framework with Channel-Independence Strategy for Traffic Forecasting—0
SEMI-CenterNet: A Machine Learning Facilitated Approach for Semiconductor Defect Inspection—0
AutoSeqRec: Autoencoder for Efficient Sequential RecommendationCode0
Localization of DOA trajectories -- Beyond the grid—0
A practical PINN framework for multi-scale problems with multi-magnitude loss termsCode1
EgoPoser: Robust Real-Time Egocentric Pose Estimation from Sparse and Intermittent Observations Everywhere—0
PETformer: Long-term Time Series Forecasting via Placeholder-enhanced TransformerCode1
JEN-1: Text-Guided Universal Music Generation with Omnidirectional Diffusion ModelsCode1
Objects do not disappear: Video object detection by single-frame object location anticipationCode1
A Hierarchical Destroy and Repair Approach for Solving Very Large-Scale Travelling Salesman Problem—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified