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 2601–2610 of 4891 papers

TitleStatusHype
Robust and Fast Bass local volatility—0
Robust Data-Driven Linear Power Flow Model with Probability Constrained Worst-Case Errors—0
Robust-DefReg: A Robust Deformable Point Cloud Registration Method based on Graph Convolutional Neural Networks—0
Robust DNN Surrogate Models with Uncertainty Quantification via Adversarial Training—0
Robust Estimation of Regression Models with Potentially Endogenous Outliers via a Modern Optimization Lens—0
Robust GAN inversion—0
Robust Hyperspectral Image Panshapring via Sparse Spatial-Spectral Representation—0
Robustifying State-space Models for Long Sequences via Approximate Diagonalization—0
Robust Low-Complexity Randomized Methods for Locating Outliers in Large Matrices—0
Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified