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 2631–2640 of 4891 papers

TitleStatusHype
Topology of surface electromyogram signals: hand gesture decoding on Riemannian manifoldsCode0
Toward Efficient and Incremental Spectral Clustering via Parametric Spectral ClusteringCode1
Bias-Reduced Neural Networks for Parameter Estimation in Quantitative MRI—0
Leveraging Hamilton-Jacobi PDEs with time-dependent Hamiltonians for continual scientific machine learningCode0
Real-Time Machine-Learning-Based Optimization Using Input Convex Long Short-Term Memory NetworkCode1
Adversarial Purification for Data-Driven Power System Event Classifiers with Diffusion Models—0
Fovea Transformer: Efficient Long-Context Modeling with Structured Fine-to-Coarse AttentionCode0
C-Procgen: Empowering Procgen with Controllable Contexts—0
Quantized Distillation: Optimizing Driver Activity Recognition Models for Resource-Constrained EnvironmentsCode1
Perfecting Liquid-State Theories with Machine Intelligence—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified