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 741–750 of 4891 papers

TitleStatusHype
Neural Interpretable PDEs: Harmonizing Fourier Insights with Attention for Scalable and Interpretable Physics DiscoveryCode1
Correlation Filters for Unmanned Aerial Vehicle-Based Aerial Tracking: A Review and Experimental EvaluationCode1
CryoAI: Amortized Inference of Poses for Ab Initio Reconstruction of 3D Molecular Volumes from Real Cryo-EM ImagesCode1
ntLink: a toolkit for de novo genome assembly scaffolding and mapping using long readsCode1
Beyond The Rainbow: High Performance Deep Reinforcement Learning on a Desktop PCCode1
Objects do not disappear: Video object detection by single-frame object location anticipationCode1
An Asynchronous Intensity Representation for Framed and Event Video SourcesCode1
Octopus Inspired Optimization Algorithm: Multi-Level Structures and Parallel Computing StrategiesCode1
Contrast-Phys+: Unsupervised and Weakly-supervised Video-based Remote Physiological Measurement via Spatiotemporal ContrastCode1
ARNN: Attentive Recurrent Neural Network for Multi-channel EEG Signals to Identify Epileptic SeizuresCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified