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 2071–2080 of 4891 papers

TitleStatusHype
Optimizing Automatic Differentiation with Deep Reinforcement Learning—0
MoE Jetpack: From Dense Checkpoints to Adaptive Mixture of Experts for Vision TasksCode2
Optimal Batched Linear BanditsCode0
Adaptive Multi-Scale Decomposition Framework for Time Series ForecastingCode2
Parameter-Inverted Image Pyramid NetworksCode2
Latent Neural Operator for Solving Forward and Inverse PDE ProblemsCode2
Monocular Localization with Semantics Map for Autonomous Vehicles—0
Enhancing Computational Efficiency of Motor Imagery BCI Classification with Block-Toeplitz Augmented Covariance Matrices and Siegel Metric—0
P-SpikeSSM: Harnessing Probabilistic Spiking State Space Models for Long-Range Dependency Tasks—0
Active ML for 6G: Towards Efficient Data Generation, Acquisition, and AnnotationCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified