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 541–550 of 4891 papers

TitleStatusHype
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
Efficient ConvBN Blocks for Transfer Learning and BeyondCode1
Principal Uncertainty Quantification with Spatial Correlation for Image Restoration ProblemsCode1
Five A^+ Network: You Only Need 9K Parameters for Underwater Image EnhancementCode1
A machine learning-based viscoelastic-viscoplastic model for epoxy nanocomposites with moisture contentCode1
MotionBEV: Attention-Aware Online LiDAR Moving Object Segmentation with Bird's Eye View based Appearance and Motion FeaturesCode1
CosmoPower-JAX: high-dimensional Bayesian inference with differentiable cosmological emulatorsCode1
SlicerTMS: Real-Time Visualization of Transcranial Magnetic Stimulation for Mental Health TreatmentCode1
Towards Better Graph Representation Learning with Parameterized Decomposition & FilteringCode1
Camera-Based HRV Prediction for Remote Learning EnvironmentsCode1
Show:102550
← PrevPage 55 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified