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 941–950 of 4891 papers

TitleStatusHype
Comply: Learning Sentences with Complex Weights inspired by Fruit Fly OlfactionCode0
P-Hologen: An End-to-End Generative Framework for Phase-Only HologramsCode0
An Interpretable Approach to Load Profile Forecasting in Power Grids using Galerkin-Approximated Koopman PseudospectraCode0
HMPNet: A Feature Aggregation Architecture for Maritime Object Detection from a Shipborne PerspectiveCode0
Hybrid Inexact BCD for Coupled Structured Matrix Factorization in Hyperspectral Super-ResolutionCode0
Learning Efficient Representations of Neutrino Telescope EventsCode0
High Dimensional Bayesian Optimization Assisted by Principal Component AnalysisCode0
A Comparison of Deep Learning Methods for Cell Detection in Digital CytologyCode0
CGKN: A Deep Learning Framework for Modeling Complex Dynamical Systems and Efficient Data AssimilationCode0
High Dimensional Bayesian Optimization using Lasso Variable SelectionCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified