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 1681–1690 of 4891 papers

TitleStatusHype
A Fast Approximate AIB Algorithm for Distributional Word Clustering—0
A computational framework for optimal and Model Predictive Control of stochastic gene regulatory networks—0
Consistent and symmetry preserving data-driven interface reconstruction for the level-set method—0
Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors—0
Consensus-based Distributed Quantum Kernel Learning for Speech Recognition—0
A Predefined-Time Convergent and Noise-Tolerant Zeroing Neural Network Model for Time Variant Quadratic Programming With Application to Robot Motion Planning—0
A Comprehensive Survey on Deep Learning Solutions for 3D Flood Mapping—0
8-bit Numerical Formats for Deep Neural Networks—0
STC-ViT: Spatio Temporal Continuous Vision Transformer for Weather Forecasting—0
Conformal testing: binary case with Markov alternatives—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified