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 3326–3350 of 4891 papers

TitleStatusHype
A Comparison of Deep Learning Architectures for Spacecraft Anomaly Detection—0
A Comprehensive Review of Techniques, Algorithms, Advancements, Challenges, and Clinical Applications of Multi-modal Medical Image Fusion for Improved Diagnosis—0
Spike-and-slab shrinkage priors for structurally sparse Bayesian neural networks—0
A Comprehensive Survey of Action Quality Assessment: Method and Benchmark—0
A Comprehensive Survey on Architectural Advances in Deep CNNs: Challenges, Applications, and Emerging Research Directions—0
A Comprehensive Survey on Deep Learning Solutions for 3D Flood Mapping—0
A computational framework for optimal and Model Predictive Control of stochastic gene regulatory networks—0
A computationally efficient reconstruction algorithm for circular cone-beam computed tomography using shallow neural networks—0
A Computational Model of Learning and Memory Using Structurally Dynamic Cellular Automata—0
A Computational Separation between Private Learning and Online Learning—0
A Consistent ICM-based χ^2 Specification Test—0
A Continual and Incremental Learning Approach for TinyML On-device Training Using Dataset Distillation and Model Size Adaption—0
A Control Oriented Fractional-Order Model of Lithium-ion Batteries Based on Caputo Definition—0
An LBP-HOG Descriptor Based on Matrix Projection For Mammogram Classification—0
A Cooperative Autoencoder for Population-Based Regularization of CNN Image Registration—0
Acoustic Source Localization with the Angular Spectrum Approach in Continuously Stratified Media—0
A Critical Synthesis of Uncertainty Quantification and Foundation Models in Monocular Depth Estimation—0
Action Recognition With Motion Diversification and Dynamic Selection—0
Action-Sufficient State Representation Learning for Control with Structural Constraints—0
ActiveInitSplat: How Active Image Selection Helps Gaussian Splatting—0
Active Learning in Video Tracking—0
Active Learning with Tabular Language Models—0
Selectively Linearized Neural Network based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems—0
Active Semi-Supervised Learning by Exploring Per-Sample Uncertainty and Consistency—0
Ada-K Routing: Boosting the Efficiency of MoE-based LLMs—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified