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 561–570 of 4891 papers

TitleStatusHype
Delving into Masked Autoencoders for Multi-Label Thorax Disease ClassificationCode1
A State-Space Perspective on Modelling and Inference for Online Skill RatingCode1
Deep Speech Synthesis from MRI-Based Articulatory RepresentationsCode1
Differentially Flat Learning-based Model Predictive Control Using a Stability, State, and Input Constraining Safety FilterCode1
DiMoSR: Feature Modulation via Multi-Branch Dilated Convolutions for Efficient Image Super-ResolutionCode1
DiRe-JAX: A JAX based Dimensionality Reduction Algorithm for Large-scale DataCode1
Deep Transfer Learning for Land Use and Land Cover Classification: A Comparative StudyCode1
A Survey of World Models for Autonomous DrivingCode1
Detach-ROCKET: Sequential feature selection for time series classification with random convolutional kernelsCode1
Distance Encoding: Design Provably More Powerful Neural Networks for Graph Representation LearningCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified