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 1161–1170 of 4891 papers

TitleStatusHype
Gaussian Ensemble Belief Propagation for Efficient Inference in High-Dimensional SystemsCode0
A Minimal Closed-Form Solution for Multi-Perspective Pose Estimation using Points and LinesCode0
Gated Fusion Network for Joint Image Deblurring and Super-ResolutionCode0
Accelerating Distributed Deep Learning using Lossless Homomorphic CompressionCode0
Gated Texture CNN for Efficient and Configurable Image DenoisingCode0
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian OptimizationCode0
Generalized Population-Based Training for Hyperparameter Optimization in Reinforcement LearningCode0
Uni-Encoder: A Fast and Accurate Response Selection Paradigm for Generation-Based Dialogue SystemsCode0
Adapting Segment Anything Model (SAM) to Experimental Datasets via Fine-Tuning on GAN-based Simulation: A Case Study in Additive ManufacturingCode0
B2EA: An Evolutionary Algorithm Assisted by Two Bayesian Optimization Modules for Neural Architecture SearchCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified