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 2211–2220 of 4891 papers

TitleStatusHype
ELF-VC: Efficient Learned Flexible-Rate Video Coding—0
Electronic excited states from physically-constrained machine learning—0
Electromyography-Based Gesture Recognition: Hierarchical Feature Extraction for Enhanced Spatial-Temporal Dynamics—0
CageViT: Convolutional Activation Guided Efficient Vision Transformer—0
An Energy-efficient Aerial Backhaul System with Reconfigurable Intelligent Surface—0
Electricity Market Forecasting via Low-Rank Multi-Kernel Learning—0
ELECTRA: A Cartesian Network for 3D Charge Density Prediction with Floating Orbitals—0
ELASTIC: Efficient Linear Attention for Sequential Interest Compression—0
Byzantine-Resilient Distributed P2P Energy Trading via Spatial-Temporal Anomaly Detection—0
An Empirical Study of Training State-of-the-Art LiDAR Segmentation Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified