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 3231–3240 of 4891 papers

TitleStatusHype
Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation—0
Resilient Set-based State Estimation for Linear Time-Invariant Systems Using ZonotopesCode0
Selectively Linearized Neural Network based RoCoF-Constrained Unit Commitment in Low-Inertia Power Systems—0
Model Predictive Control for Signal Temporal Logic Specifications with Time Interval DecompositionCode1
A Survey on the Integration of Machine Learning with Sampling-based Motion Planning—0
Edge2Vec: A High Quality Embedding for the Jigsaw Puzzle Problem—0
Evaluating Distribution System Reliability with Hyperstructures Graph Convolutional Nets—0
Zero-shot Image Captioning by Anchor-augmented Vision-Language Space Alignment—0
Structured Singular Value of a Repeated Complex Full-Block Uncertainty—0
Soft-Landing Strategy for Alleviating the Task Discrepancy Problem in Temporal Action Localization TasksCode0
Show:102550
← PrevPage 324 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified