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 3691–3700 of 4891 papers

TitleStatusHype
Real-time decision-making for autonomous vehicles under faults—0
EvoPruneDeepTL: An Evolutionary Pruning Model for Transfer Learning based Deep Neural NetworksCode0
B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture SearchCode0
TorchMD-NET: Equivariant Transformers for Neural Network based Molecular Potentials—0
DEVO: Depth-Event Camera Visual Odometry in Challenging Conditions—0
On the Complexity of Winner Determination and Strategic Control in Conditional Approval Voting—0
Mold into a Graph: Efficient Bayesian Optimization over Mixed-SpacesCode0
AdaAnn: Adaptive Annealing Scheduler for Probability Density ApproximationCode0
Weisfeiler and Leman Go Infinite: Spectral and Combinatorial Pre-ColoringsCode0
Differentially Private Community Detection for Stochastic Block Models—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified