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 2871–2880 of 4891 papers

TitleStatusHype
Transport Equation based Physics Informed Neural Network to predict the Yield Strength of Architected Materials—0
Monaural Multi-Speaker Speech Separation Using Efficient Transformer Model—0
TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones—0
From continuous-time formulations to discretization schemes: tensor trains and robust regression for BSDEs and parabolic PDEsCode1
Developing and Evaluating Tiny to Medium-Sized Turkish BERT Models—0
US \& MRI Image Fusion Based on Markerless Skin Registration—0
Federated K-Means Clustering via Dual Decomposition-based Distributed Optimization—0
Universality of Linear Recurrences Followed by Non-linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues—0
Variational Autoencoding of Dental Point CloudsCode1
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety FilterCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified