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 571–580 of 4891 papers

TitleStatusHype
A Hybrid CNN-BiLSTM Voice Activity DetectorCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
DnS: Distill-and-Select for Efficient and Accurate Video Indexing and RetrievalCode1
Dynamic Group Convolution for Accelerating Convolutional Neural NetworksCode1
DeepSeeColor: Realtime Adaptive Color Correction for Autonomous Underwater Vehicles via Deep Learning MethodsCode1
Deep reinforcement learning for large-scale epidemic controlCode1
Deep Speech Synthesis from MRI-Based Articulatory RepresentationsCode1
Efficient Aggregated Kernel Tests using Incomplete U-statisticsCode1
DeePoly: A High-Order Accuracy Scientific Machine Learning Framework for Function Approximation and Solving PDEsCode1
Deep Learning for Hate Speech Detection: A Comparative StudyCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified