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 3961–3970 of 4891 papers

TitleStatusHype
Fast and Scalable Earth Texture Synthesis using Spatially Assembled Generative Adversarial Neural Networks—0
A Variational Infinite Mixture for Probabilistic Inverse Dynamics LearningCode1
MAGIC: Learning Macro-Actions for Online POMDP PlanningCode1
Support estimation in high-dimensional heteroscedastic mean regression—0
Transfer Function Analysis and Implementation of Active Disturbance Rejection Control—0
Multi\^2OIE: Multilingual Open Information Extraction Based on Multi-Head Attention with BERTCode1
A Simple Local Minimal Intensity Prior and An Improved Algorithm for Blind Image DeblurringCode1
Non-Iterative Blind Calibration of Nested Arrays with Asymptotically Optimal Weighting—0
A Data-Driven Sparse Polynomial Chaos Expansion Method to Assess Probabilistic Total Transfer Capability for Power Systems with Renewables—0
A Domain-Shrinking based Bayesian Optimization Algorithm with Order-Optimal Regret PerformanceCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified