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 2791–2800 of 4891 papers

TitleStatusHype
Solving Seismic Wave Equations on Variable Velocity Models with Fourier Neural Operator—0
Some New Results for Poisson Binomial Models—0
SourceDetMamba: A Graph-aware State Space Model for Source Detection in Sequential Hypergraphs—0
Soybean Disease Detection via Interpretable Hybrid CNN-GNN: Integrating MobileNetV2 and GraphSAGE with Cross-Modal Attention—0
SPAR3D: Stable Point-Aware Reconstruction of 3D Objects from Single Images—0
Sparse Approximate Manifolds for Differential Geometric MCMC—0
Sparse Bayesian Learning-Based Hierarchical Construction for 3D Radio Environment Maps Incorporating Channel Shadowing—0
Sparse Canonical Correlation Analysis via Concave Minimization—0
Sparse Coding on Cascaded Residuals—0
Sparse Convolutional Recurrent Learning for Efficient Event-based Neuromorphic Object Detection—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified