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 3931–3940 of 4891 papers

TitleStatusHype
Combining distribution-based neural networks to predict weather forecast probabilitiesCode0
Online Learning Koopman operator for closed-loop electrical neurostimulation in epilepsy—0
Parallel Model Exploration for Tumor Treatment SimulationsCode0
Distributed Experiment Design and Control for Multi-agent Systems with Gaussian Processes—0
A VAE-Bayesian Deep Learning Scheme for Solar Generation Forecasting based on Dimensionality Reduction—0
Sinusoidal Parameter Estimation from Signed Measurements via Majorization-Minimization Based RELAX—0
Forward and Backward Bellman equations improve the efficiency of EM algorithm for DEC-POMDP—0
LSDAT: Low-Rank and Sparse Decomposition for Decision-based Adversarial Attack—0
DCF-ASN: Coarse-to-fine Real-time Visual Tracking via Discriminative Correlation Filter and Attentional Siamese Network—0
K-expectiles clustering—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified