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 111–120 of 4891 papers

TitleStatusHype
Offline RL with Smooth OOD Generalization in Convex Hull and its NeighborhoodCode0
Rethinking Range-View LiDAR Segmentation in Adverse Weather—0
KARMA: A Multilevel Decomposition Hybrid Mamba Framework for Multivariate Long-Term Time Series ForecastingCode1
RuleReasoner: Reinforced Rule-based Reasoning via Domain-aware Dynamic SamplingCode1
NeurIPS 2024 ML4CFD Competition: Results and Retrospective Analysis—0
Local MDI+: Local Feature Importances for Tree-Based Models—0
IMAGIC-500: IMputation benchmark on A Generative Imaginary Country (500k samples)Code0
sparseGeoHOPCA: A Geometric Solution to Sparse Higher-Order PCA Without Covariance Estimation—0
TS-PIELM: Time-Stepping Physics-Informed Extreme Learning Machine Facilitates Soil Consolidation Analyses—0
HyColor: An Efficient Heuristic Algorithm for Graph Coloring—0
Show:102550
← PrevPage 12 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified