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 2701–2710 of 4891 papers

TitleStatusHype
Applications of ML-Based Surrogates in Bayesian Approaches to Inverse Problems—0
spateGAN: Spatio-Temporal Downscaling of Rainfall Fields Using a cGAN ApproachCode0
Effortless Cross-Platform Video Codec: A Codebook-Based Method—0
TpopT: Efficient Trainable Template Optimization on Low-Dimensional Manifolds—0
Efficient and Effective Deep Multi-view Subspace Clustering—0
Merging Experts into One: Improving Computational Efficiency of Mixture of ExpertsCode1
Re-initialization-free Level Set Method via Molecular Beam Epitaxy Equation Regularization for Image Segmentation—0
QUIK: Towards End-to-End 4-Bit Inference on Generative Large Language ModelsCode1
Fast Word Error Rate Estimation Using Self-Supervised Representations for Speech and Text—0
QArchSearch: A Scalable Quantum Architecture Search Package—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified