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 2271–2280 of 4891 papers

TitleStatusHype
Neuromorphic Spintronics—0
Scaling Continuous Kernels with Sparse Fourier Domain Learning—0
OML-AD: Online Machine Learning for Anomaly Detection in Time Series DataCode0
Multiscale fusion enhanced spiking neural network for invasive BCI neural signal decoding—0
Integration of Mamba and Transformer -- MAT for Long-Short Range Time Series Forecasting with Application to Weather Dynamics—0
An Efficient Privacy-aware Split Learning Framework for Satellite Communications—0
Adaptive Sampling for Continuous Group Equivariant Neural Networks—0
Biomimetic Frontend for Differentiable Audio ProcessingCode0
Thermal Modelling of Battery Cells for Optimal Tab and Surface Cooling Control—0
Convex Reformulation of Information Constrained Linear State Estimation with Mixed-Binary Variables for Outlier Accommodation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified