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

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Showing 4341–4350 of 4891 papers

TitleStatusHype
Imitation Learning of Neural Spatio-Temporal Point ProcessesCode0
Warping Resilient Scalable Anomaly Detection in Time Series—0
FAMED-Net: A Fast and Accurate Multi-scale End-to-end Dehazing NetworkCode0
Learning Gaussian Graphical Models with Ordered Weighted L1 RegularizationCode0
A Robust Roll Angle Estimation Algorithm Based on Gradient Descent—0
Self-Attentional Models for Lattice Inputs—0
GAMMA: A General Agent Motion Model for Autonomous DrivingCode0
3D Shape Reconstruction From Images in the Frequency Domain—0
Analysis of high-dimensional Continuous Time Markov Chains using the Local Bouncy Particle Sampler—0
Learning Navigation Subroutines from Egocentric Videos—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified