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 2911–2920 of 4891 papers

TitleStatusHype
Large-scale Bayesian Structure Learning for Gaussian Graphical Models using Marginal Pseudo-likelihoodCode0
Scalable method for Bayesian experimental design without integrating over posterior distributionCode0
RL4CO: an Extensive Reinforcement Learning for Combinatorial Optimization BenchmarkCode4
Approximate Dynamic Programming for Constrained Piecewise Affine Systems with Stability and Safety Guarantees—0
What Truly Matters in Trajectory Prediction for Autonomous Driving?—0
DNABERT-2: Efficient Foundation Model and Benchmark For Multi-Species GenomeCode2
A denoised Mean Teacher for domain adaptive point cloud registrationCode0
Verification of Neural Network Control Systems using Symbolic Zonotopes and Polynotopes—0
Scaling MLPs: A Tale of Inductive BiasCode1
PathMLP: Smooth Path Towards High-order HomophilyCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified