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 2901–2910 of 4891 papers

TitleStatusHype
Joint Hierarchical Priors and Adaptive Spatial Resolution for Efficient Neural Image Compression—0
Contextualizing MLP-Mixers Spatiotemporally for Urban Data Forecast at ScaleCode1
Learning Difference Equations with Structured Grammatical Evolution for Postprandial Glycaemia Prediction—0
TopicFM+: Boosting Accuracy and Efficiency of Topic-Assisted Feature MatchingCode1
On efficient computation in active inferenceCode1
SUGAR: Spherical Ultrafast Graph Attention Framework for Cortical Surface Registration—0
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations—0
DeepMediX: A Deep Learning-Driven Resource-Efficient Medical Diagnosis Across the SpectrumCode0
Weighted Anisotropic-Isotropic Total Variation for Poisson DenoisingCode0
Practical and Asymptotically Exact Conditional Sampling in Diffusion ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified