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

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Showing 491–500 of 4891 papers

TitleStatusHype
Deep fiber clustering: Anatomically informed fiber clustering with self-supervised deep learning for fast and effective tractography parcellationCode1
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
MoViNets: Mobile Video Networks for Efficient Video RecognitionCode1
mPLUG: Effective and Efficient Vision-Language Learning by Cross-modal Skip-connectionsCode1
Multi^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERTCode1
Multi\^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERTCode1
DeepZero: Scaling up Zeroth-Order Optimization for Deep Model TrainingCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
Multi-Objective Evolutionary Design of Deep Convolutional Neural Networks for Image ClassificationCode1
DeformUX-Net: Exploring a 3D Foundation Backbone for Medical Image Segmentation with Depthwise Deformable ConvolutionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified