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 2481–2490 of 4891 papers

TitleStatusHype
OpenSlot: Mixed Open-Set Recognition with Object-Centric Learning—0
Classification of Power Quality Disturbances Using Resnet with Channel Attention Mechanism—0
UltraPixel: Advancing Ultra-High-Resolution Image Synthesis to New Peaks—0
On Statistical Rates and Provably Efficient Criteria of Latent Diffusion Transformers (DiTs)—0
Trajectory Tracking for UAVs: An Interpolating Control Approach—0
Efficient Automated Circuit Discovery in Transformers using Contextual Decomposition—0
Multifidelity Cross-validation—0
PointViG: A Lightweight GNN-based Model for Efficient Point Cloud Analysis—0
SpectralKAN: Kolmogorov-Arnold Network for Hyperspectral Images Change DetectionCode0
NeurIPS 2024 ML4CFD Competition: Harnessing Machine Learning for Computational Fluid Dynamics in Airfoil Design—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified