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 1271–1280 of 4891 papers

TitleStatusHype
FrameRS: A Video Frame Compression Model Composed by Self supervised Video Frame Reconstructor and Key Frame SelectorCode0
GTG-Shapley: Efficient and Accurate Participant Contribution Evaluation in Federated LearningCode0
FREEtree: A Tree-based Approach for High Dimensional Longitudinal Data With Correlated FeaturesCode0
A Triple-Inertial Accelerated Alternating Optimization Method for Deep Learning TrainingCode0
Differentiable probabilistic models of scientific imaging with the Fourier slice theoremCode0
Missing Data Imputation Based on Dynamically Adaptable Structural Equation Modeling with Self-AttentionCode0
Reachability Analysis Using Constrained Polynomial Logical ZonotopesCode0
Regression modelling of spatiotemporal extreme U.S. wildfires via partially-interpretable neural networksCode0
FORTRESS: Function-composition Optimized Real-Time Resilient Structural Segmentation via Kolmogorov-Arnold Enhanced Spatial Attention NetworksCode0
DeepRTE: Pre-trained Attention-based Neural Network for Radiative TranferCode0
Show:102550
← PrevPage 128 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified