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 1261–1270 of 4891 papers

TitleStatusHype
AdaAnn: Adaptive Annealing Scheduler for Probability Density ApproximationCode0
Development of a skateboarding trick classifier using accelerometry and machine learningCode0
From Roots to Rewards: Dynamic Tree Reasoning with RLCode0
GCNv2: Efficient Correspondence Prediction for Real-Time SLAMCode0
Attention-Aware Laparoscopic Image Desmoking Network with Lightness Embedding and Hybrid Guided EmbeddingCode0
Graph Neural Networks for modelling breast biomechanical compressionCode0
Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse AttentionCode0
GraphQA: Protein Model Quality Assessment using Graph Convolutional NetworkCode0
Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-AttentionCode0
Attentional Correlation Filter Network for Adaptive Visual TrackingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified