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 4301–4310 of 4891 papers

TitleStatusHype
Deep Coarse-to-fine Dense Light Field Reconstruction with Flexible Sampling and Geometry-aware FusionCode0
A Nonconvex Approach for Exact and Efficient Multichannel Sparse Blind DeconvolutionCode0
A Multiple Source Hourglass Deep Network for Multi-Focus Image Fusion—0
A novel active learning-based Gaussian process metamodelling strategy for estimating the full probability distribution in forward UQ analysis—0
Neuromorphic Electronic Systems for Reservoir Computing—0
Region Tracking in an Image Sequence: Preventing Driver Inattention—0
Applications of Nature-Inspired Algorithms for Dimension Reduction: Enabling Efficient Data Analytics—0
Action recognition with spatial-temporal discriminative filter banks—0
Musical Rhythm Transcription Based on Bayesian Piece-Specific Score Models Capturing Repetitions—0
Improved Techniques for Training Adaptive Deep NetworksCode1
Show:102550
← PrevPage 431 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified