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 741–750 of 4891 papers

TitleStatusHype
SE(3) Equivariant Graph Neural Networks with Complete Local FramesCode1
Equivariant Hypergraph Diffusion Neural OperatorsCode1
InternVL-X: Advancing and Accelerating InternVL Series with Efficient Visual Token CompressionCode1
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic ModelsCode1
Hyperspectral Pansharpening: Critical Review, Tools and Future PerspectivesCode1
RGB-Event Fusion with Self-Attention for Collision PredictionCode1
An Asynchronous Intensity Representation for Framed and Event Video SourcesCode1
Towards Reliable Medical Image Segmentation by utilizing Evidential Calibrated UncertaintyCode1
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Boosting Light-Weight Depth Estimation Via Knowledge DistillationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified