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 2601–2610 of 4891 papers

TitleStatusHype
Graphlets correct for the topological information missed by random walks—0
Computation-efficient Virtual Sensing Approach with Multichannel Adjoint Least Mean Square Algorithm—0
LiteVAE: Lightweight and Efficient Variational Autoencoders for Latent Diffusion Models—0
Global-local Fourier Neural Operator for Accelerating Coronal Magnetic Field ModelCode0
Enhancing Transformer-based models for Long Sequence Time Series Forecasting via Structured MatrixCode0
Learning Causal Dynamics Models in Object-Oriented EnvironmentsCode0
3DSS-Mamba: 3D-Spectral-Spatial Mamba for Hyperspectral Image Classification—0
Multiscale lubrication simulation based on fourier feature networks with trainable frequency—0
Graph neural networks informed locally by thermodynamicsCode0
Efficient Economic Model Predictive Control of Water Treatment Process with Learning-based Koopman Operator—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified