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 3581–3590 of 4891 papers

TitleStatusHype
Combining Retrospective Approximation with Importance Sampling for Optimising Conditional Value at Risk—0
Temporal Attention Unit: Towards Efficient Spatiotemporal Predictive Learning—0
TreeDRNet:A Robust Deep Model for Long Term Time Series Forecasting—0
Superadditivity and Convex Optimization for Globally Optimal Cell Segmentation using Deformable Shape ModelsCode0
Efficient fine-grained road segmentation using superpixel-based CNN and CRF models—0
Square One Bias in NLP: Towards a Multi-Dimensional Exploration of the Research Manifold—0
Digital Twin Data Modelling by Randomized Orthogonal Decomposition and Deep Learning—0
Fast Simulation of Particulate Suspensions Enabled by Graph Neural Network—0
Fast and Reliable Evaluation of Adversarial Robustness with Minimum-Margin AttackCode0
Reliability Analysis of Complex Multi-State System Based on Universal Generating Function and Bayesian Network—0
Show:102550
← PrevPage 359 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified