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 2091–2100 of 4891 papers

TitleStatusHype
Wasserstein Distributionally Robust Control and State Estimation for Partially Observable Linear Systems—0
Learning Decision Trees and Forests with Algorithmic RecourseCode0
RaDe-GS: Rasterizing Depth in Gaussian SplattingCode4
Multimodal Deep Learning for Low-Resource Settings: A Vector Embedding Alignment Approach for Healthcare Applications—0
Exploiting Frequency Correlation for Hyperspectral Image Reconstruction—0
Modeling Randomly Observed Spatiotemporal Dynamical Systems—0
A Batch Sequential Halving Algorithm without Performance Degradation—0
Pedestrian intention prediction in Adverse Weather Conditions with Spiking Neural Networks and Dynamic Vision Sensors—0
From Structured to Unstructured:A Comparative Analysis of Computer Vision and Graph Models in solving Mesh-based PDEs—0
An Efficient Multi Quantile Regression Network with Ad Hoc Prevention of Quantile Crossing—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified