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 2781–2790 of 4891 papers

TitleStatusHype
Optimizing Deep Decarbonization Pathways in California with Power System Planning Using Surrogate Level-based Lagrangian Relaxation—0
Native Language Identification with Big Bird EmbeddingsCode0
Contrast-Phys+: Unsupervised and Weakly-supervised Video-based Remote Physiological Measurement via Spatiotemporal ContrastCode1
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion ModelsCode0
Hybrid Algorithm Selection and Hyperparameter Tuning on Distributed Machine Learning Resources: A Hierarchical Agent-based Approach—0
Computation of safe disturbance sets using implicit RPI sets—0
Geometry Enhanced Optimal Control Technique for Acrobatic Flip Motion of Quadcopter—0
Effective Real Image Editing with Accelerated Iterative Diffusion Inversion—0
LMBiS-Net: A Lightweight Multipath Bidirectional Skip Connection based CNN for Retinal Blood Vessel SegmentationCode0
HAct: Out-of-Distribution Detection with Neural Net Activation Histograms—0
Show:102550
← PrevPage 279 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified