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 241–250 of 4891 papers

TitleStatusHype
Efficient and Information-Preserving Future Frame Prediction and BeyondCode1
End-to-end Prostate Cancer Detection in bpMRI via 3D CNNs: Effects of Attention Mechanisms, Clinical Priori and Decoupled False Positive ReductionCode1
Enhancing Fast Feed Forward Networks with Load Balancing and a Master Leaf NodeCode1
Efficient Multi-scale Network with Learnable Discrete Wavelet Transform for Blind Motion DeblurringCode1
Electronic-structure properties from atom-centered predictions of the electron densityCode1
SE(3) Equivariant Graph Neural Networks with Complete Local FramesCode1
Event-based Video Reconstruction via Potential-assisted Spiking Neural NetworkCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Efficient Aggregated Kernel Tests using Incomplete U-statisticsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified