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 1711–1720 of 4891 papers

TitleStatusHype
Memory Networks: Towards Fully Biologically Plausible Learning—0
RockTrack: A 3D Robust Multi-Camera-Ken Multi-Object Tracking FrameworkCode2
Applications of Knowledge Distillation in Remote Sensing: A Survey—0
ReLU Surrogates in Mixed-Integer MPC for Irrigation Scheduling—0
On Vision Transformers for Classification Tasks in Side-Scan Sonar Imagery—0
SPRMamba: Surgical Phase Recognition for Endoscopic Submucosal Dissection with MambaCode0
Axial Attention Transformer Networks: A New Frontier in Breast Cancer Detection—0
Recurrent Interpolants for Probabilistic Time Series Prediction—0
PropEnc: A Property Encoder for Graph Neural Networks—0
A computational framework for optimal and Model Predictive Control of stochastic gene regulatory networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified