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 3161–3170 of 4891 papers

TitleStatusHype
Graph Mixer NetworksCode1
AudioLDM: Text-to-Audio Generation with Latent Diffusion ModelsCode4
Optimizing a Bayesian method for estimating the Hurst exponent in behavioral sciences—0
Maximum Optimality Margin: A Unified Approach for Contextual Linear Programming and Inverse Linear ProgrammingCode0
Rewarded meta-pruning: Meta Learning with Rewards for Channel PruningCode0
RD-NAS: Enhancing One-shot Supernet Ranking Ability via Ranking Distillation from Zero-cost ProxiesCode1
Optimising Event-Driven Spiking Neural Network with Regularisation and CutoffCode1
Out-of-Distribution Detection based on In-Distribution Data Patterns Memorization with Modern Hopfield EnergyCode0
Data-Driven Distributionally Robust Scheduling of Community Integrated Energy Systems with Uncertain Renewable Generations Considering Integrated Demand Response—0
ntLink: a toolkit for de novo genome assembly scaffolding and mapping using long readsCode1
Show:102550
← PrevPage 317 of 490Next →

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified