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 281–290 of 4891 papers

TitleStatusHype
EViT: An Eagle Vision Transformer with Bi-Fovea Self-AttentionCode1
Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent CodingCode1
Estimating Koopman operators with sketching to provably learn large scale dynamical systemsCode1
SE(3) Equivariant Graph Neural Networks with Complete Local FramesCode1
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic ModelsCode1
Exploiting Deblurring Networks for Radiance FieldsCode1
Faith-Shap: The Faithful Shapley Interaction IndexCode1
BetterNet: An Efficient CNN Architecture with Residual Learning and Attention for Precision Polyp SegmentationCode1
Benchmarking the Robustness of Spatial-Temporal Models Against CorruptionsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified