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 711–720 of 4891 papers

TitleStatusHype
Solving high-dimensional parabolic PDEs using the tensor train formatCode1
You Only Compress Once: Optimal Data Compression for Estimating Linear ModelsCode1
Efficient Two-Stream Network for Violence Detection Using Separable Convolutional LSTMCode1
Subdimensional Expansion for Multi-objective Multi-agent Path FindingCode1
CobBO: Coordinate Backoff Bayesian Optimization with Two-Stage KernelsCode1
End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive ReductionCode1
StainNet: a fast and robust stain normalization networkCode1
INSPIRE: Intensity and spatial information-based deformable image registrationCode1
An empirical evaluation of functional alignment using inter-subject decodingCode1
EXTENDING CONDITIONAL CONVOLUTION STRUCTURES FOR ENHANCING MULTITASKING CONTINUAL LEARNINGCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified