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 3281–3290 of 4891 papers

TitleStatusHype
Coil Sketching for computationally-efficient MR iterative reconstruction—0
Medical supervised masked autoencoders: Crafting a better masking strategy and efficient fine-tuning schedule for medical image classificationCode0
Treasure What You Have: Exploiting Similarity in Deep Neural Networks for Efficient Video Processing—0
TaLU: A Hybrid Activation Function Combining Tanh and Rectified Linear Unit to Enhance Neural NetworksCode0
RFR-WWANet: Weighted Window Attention-Based Recovery Feature Resolution Network for Unsupervised Image RegistrationCode0
A 3D grain-based reconstruction method from a 2D surface image for the Distinct Lattice Spring Model—0
A numerically efficient output-only system-identification framework for stochastically forced self-sustained oscillators—0
Near-Field MIMO-ISAR Millimeter-Wave Imaging—0
Beyond Prediction: On-street Parking Recommendation using Heterogeneous Graph-based List-wise RankingCode0
Physics-Guided Graph Neural Networks for Real-time AC/DC Power Flow Analysis—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified