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 1731–1740 of 4891 papers

TitleStatusHype
Scaling Continuous Kernels with Sparse Fourier Domain Learning—0
Multiscale fusion enhanced spiking neural network for invasive BCI neural signal decoding—0
On the limits of agency in agent-based modelsCode4
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
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
Apollo: Band-sequence Modeling for High-Quality Audio RestorationCode3
Integration of Mamba and Transformer -- MAT for Long-Short Range Time Series Forecasting with Application to Weather Dynamics—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified