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 1991–2000 of 4891 papers

TitleStatusHype
Trajectory Tracking for UAVs: An Interpolating Control Approach—0
Multifidelity Cross-validation—0
PointViG: A Lightweight GNN-based Model for Efficient Point Cloud Analysis—0
Hyperspectral Pansharpening: Critical Review, Tools and Future PerspectivesCode1
SpectralKAN: Kolmogorov-Arnold Network for Hyperspectral Images Change DetectionCode0
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)—0
Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition—0
NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design—0
PolygonGNN: Representation Learning for Polygonal Geometries with Heterogeneous Visibility GraphCode1
Aeroengine performance prediction using a physical-embedded data-driven method—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified