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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 2226–2250 of 4891 papers

TitleStatusHype
A Hybrid Virtual Element Method and Deep Learning Approach for Solving One-Dimensional Euler-Bernoulli Beams—0
LGBQPC: Local Granular-Ball Quality Peaks Clustering—0
Imperfect Vision Encoders: Efficient and Robust Tuning for Vision-Language Models—0
Importance Filtering with Risk Models for Complex Driving Situations—0
Deep Fusion of Ultra-Low-Resolution Thermal Camera and Gyroscope Data for Lighting-Robust and Compute-Efficient Rotational Odometry—0
DeepFracture: A Generative Approach for Predicting Brittle Fractures with Neural Discrete Representation Learning—0
A Refined Equilibrium Generative Adversarial Network for Retinal Vessel Segmentation—0
Deep FisherNet for Object Classification—0
DeepF-fNet: a physics-informed neural network for vibration isolation optimization—0
A Hybrid Two-layer Feature Selection Method Using GeneticAlgorithm and Elastic Net—0
A Symbolic and Statistical Learning Framework to Discover Bioprocessing Regulatory Mechanism: Cell Culture Example—0
Deep Dynamics: Vehicle Dynamics Modeling with a Physics-Constrained Neural Network for Autonomous Racing—0
A hybrid neural network for real-time OD demand calibration under disruptions—0
Deep Convolutional Neural Networks: A survey of the foundations, selected improvements, and some current applications—0
A Survey on Vietnamese Document Analysis and Recognition: Challenges and Future Directions—0
Imbalanced biomedical data classification using self-adaptive multilayer ELM combined with dynamic GAN—0
Learning-based Robust Motion Planning with Guaranteed Stability: A Contraction Theory Approach—0
NeuralFactors: A Novel Factor Learning Approach to Generative Modeling of Equities—0
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning—0
Image Denoising via Multi-scale Nonlinear Diffusion Models—0
Deep Bag-of-Words Model: An Efficient and Interpretable Relevance Architecture for Chinese E-Commerce—0
A Survey on Computationally Efficient Neural Architecture Search—0
A Hybrid Mixture of t-Factor Analyzers for Clustering High-dimensional Data—0
Image edge enhancement for effective image classification—0
Deep Auto-Deferring Policy for Combinatorial Optimization—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified