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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2371–2380 of 4891 papers

TitleStatusHype
Robust Model Predictive Control for Aircraft Intent-Aware Collision Avoidance—0
Information Geometry and Beta Link for Optimizing Sparse Variational Student-t Processes—0
Event-Stream Super Resolution using Sigma-Delta Neural Network—0
Enhancing Diabetic Retinopathy Diagnosis: A Lightweight CNN Architecture for Efficient Exudate Detection in Retinal Fundus Images—0
A hybrid neural network for real-time OD demand calibration under disruptions—0
Prioritizing Modalities: Flexible Importance Scheduling in Federated Multimodal Learning—0
Body Transformer: Leveraging Robot Embodiment for Policy Learning—0
Inferring directed spectral information flow between mixed-frequency time seriesCode0
InfLocNet: Enhanced Lung Infection Localization and Disease Detection from Chest X-Ray Images Using Lightweight Deep Learning—0
Single Image Dehazing Using Scene Depth Ordering—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified