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 491–500 of 4891 papers

TitleStatusHype
FilterTS: Comprehensive Frequency Filtering for Multivariate Time Series ForecastingCode1
MRI super-resolution reconstruction using efficient diffusion probabilistic model with residual shiftingCode1
MSFMamba: Multi-Scale Feature Fusion State Space Model for Multi-Source Remote Sensing Image ClassificationCode1
MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and ClassificationCode1
Finer-CAM: Spotting the Difference Reveals Finer Details for Visual ExplanationCode1
Efficient Multi-agent Reinforcement Learning by PlanningCode1
A prediction and behavioural analysis of machine learning methods for modelling travel mode choiceCode1
FedPop: Federated Population-based Hyperparameter TuningCode1
FedSSA: Semantic Similarity-based Aggregation for Efficient Model-Heterogeneous Personalized Federated LearningCode1
A new computationally efficient algorithm to solve Feature Selection for Functional Data Classification in high-dimensional spacesCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified