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 531–540 of 4891 papers

TitleStatusHype
HabiCrowd: A High Performance Simulator for Crowd-Aware Visual NavigationCode1
From NeRFLiX to NeRFLiX++: A General NeRF-Agnostic Restorer ParadigmCode1
Hexatagging: Projective Dependency Parsing as TaggingCode1
An adaptive augmented Lagrangian method for training physics and equality constrained artificial neural networksCode1
Estimating Koopman operators with sketching to provably learn large scale dynamical systemsCode1
FAMO: Fast Adaptive Multitask OptimizationCode1
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
Beyond Regular Grids: Fourier-Based Neural Operators on Arbitrary DomainsCode1
Neural incomplete factorization: learning preconditioners for the conjugate gradient methodCode1
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified