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 2061–2070 of 4891 papers

TitleStatusHype
Trustworthy and Practical AI for Healthcare: A Guided Deferral System with Large Language Models—0
Data-driven Power Flow Linearization: Theory—0
Economic Model Predictive Control of Water Distribution Systems with Accelerated Optimization Algorithm—0
Data-driven Power Flow Linearization: Simulation—0
Computational and Statistical Guarantees for Tensor-on-Tensor Regression with Tensor Train Decomposition—0
HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space ModelCode0
Vision Mamba: Cutting-Edge Classification of Alzheimer's Disease with 3D MRI Scans—0
Cross Language Soccer Framework: An Open Source Framework for the RoboCup 2D Soccer SimulationCode0
RAPID: Robust APT Detection and Investigation Using Context-Aware Deep Learning—0
Bayesian Structural Model Updating with Multimodal Variational Autoencoder—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified