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 3201–3210 of 4891 papers

TitleStatusHype
VNI-Net: Vector Neurons-based Rotation-Invariant Descriptor for LiDAR Place Recognition—0
Volumetric 3D Tracking by Detection—0
VORTEX: A Spatial Computing Framework for Optimized Drone Telemetry Extraction from First-Person View Flight Data—0
Wait-Less Offline Tuning and Re-solving for Online Decision Making—0
WaKA: Data Attribution using K-Nearest Neighbors and Membership Privacy Principles—0
Walking with Perception: Efficient Random Walk Sampling via Common Neighbor Awareness—0
Warping Resilient Scalable Anomaly Detection in Time Series—0
Wasserstein Adaptive Value Estimation for Actor-Critic Reinforcement Learning—0
Wasserstein Distributionally Robust Control and State Estimation for Partially Observable Linear Systems—0
Wave (from) Polarized Light Learning (WPLL) method: high resolution spatio-temporal measurements of water surface waves in laboratory setups—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified