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 1101–1110 of 4891 papers

TitleStatusHype
A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams—0
Generalized and Efficient 2D Gaussian Splatting for Arbitrary-scale Super-ResolutionCode2
A Short-Term Predict-Then-Cluster Framework for Meal Delivery Services—0
Flash Window Attention: speedup the attention computation for Swin TransformerCode1
A Hybrid Framework for Reinsurance Optimization: Integrating Generative Models and Reinforcement LearningCode0
GenMol: A Drug Discovery Generalist with Discrete Diffusion—0
Efficient Representations for High-Cardinality Categorical Variables in Machine Learning—0
Universal-2-TF: Robust All-Neural Text Formatting for ASR—0
FLowHigh: Towards Efficient and High-Quality Audio Super-Resolution with Single-Step Flow MatchingCode2
Enhanced Quantile Regression with Spiking Neural Networks for Long-Term System Health Prognostics—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified