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 3071–3080 of 4891 papers

TitleStatusHype
Polarity is all you need to learn and transfer fasterCode0
Efficient Alternating Minimization Solvers for Wyner Multi-View Unsupervised LearningCode0
On the Importance of Feature Separability in Predicting Out-Of-Distribution Error—0
GP-PCS: One-shot Feature-Preserving Point Cloud Simplification with Gaussian Processes on Riemannian ManifoldsCode0
Heat flux for semi-local machine-learning potentialsCode1
EfficientAD: Accurate Visual Anomaly Detection at Millisecond-Level LatenciesCode2
Marching-Primitives: Shape Abstraction from Signed Distance FunctionCode1
NVAutoNet: Fast and Accurate 360^ 3D Visual Perception For Self Driving—0
Revisiting DeepFool: generalization and improvementCode0
Hardness of Independent Learning and Sparse Equilibrium Computation in Markov Games—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified