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 3771–3780 of 4891 papers

TitleStatusHype
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networksCode1
Federated Learning for Short-term Residential Load Forecasting—0
One4all User Representation for Recommender Systems in E-commerce—0
Revisiting 2D Convolutional Neural Networks for Graph-based Applications—0
Combining Recurrent, Convolutional, and Continuous-time Models with Linear State Space Layers—0
Deep learning of transition probability densities for stochastic asset models with applications in option pricing—0
Statistical Optimality and Computational Efficiency of Nyström Kernel PCA—0
Vision Transformer for Fast and Efficient Scene Text RecognitionCode1
Sparse solutions of the kernel herding algorithm by improved gradient approximation—0
An even-load-distribution design for composite bolted joints using a novel circuit model and artificial neural networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified