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 4411–4420 of 4891 papers

TitleStatusHype
EPNet: An Efficient Pyramid Network for Enhanced Single-Image Super-Resolution with Reduced Computational Requirements—0
EPS-MoE: Expert Pipeline Scheduler for Cost-Efficient MoE Inference—0
Equiangular Kernel Dictionary Learning With Applications to Dynamic Texture Analysis—0
Application of Spherical Convolutional Neural Networks to Image Reconstruction and Denoising in Nuclear Medicine—0
Equivariant Transformers for Neural Network based Molecular Potentials—0
ERes2NetV2: Boosting Short-Duration Speaker Verification Performance with Computational Efficiency—0
Ergodic Inference: Accelerate Convergence by Optimisation—0
ERNIE-ViL 2.0: Multi-view Contrastive Learning for Image-Text Pre-training—0
EROAM: Event-based Camera Rotational Odometry and Mapping in Real-time—0
Error Analysis of Generalized Nyström Kernel Regression—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified