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 721–730 of 4891 papers

TitleStatusHype
Linear Reduced Order Model Predictive ControlCode1
Multi-stage Attention ResU-Net for Semantic Segmentation of Fine-Resolution Remote Sensing ImagesCode1
Multi-Features Guidance Network for partial-to-partial point cloud registrationCode1
Augmented Lagrangian Adversarial AttacksCode1
A Variational Infinite Mixture for Probabilistic Inverse Dynamics LearningCode1
MAGIC: Learning Macro-Actions for Online POMDP PlanningCode1
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
Federated Bayesian Optimization via Thompson SamplingCode1
Efficient and Compact Convolutional Neural Network Architectures for Non-temporal Real-time Fire DetectionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified