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 3491–3500 of 4891 papers

TitleStatusHype
Latent Temporal Flows for Multivariate Analysis of Wearables Data—0
An Efficient FPGA Accelerator for Point Cloud—0
Graph Neural Network Surrogate for Seismic Reliability Analysis of Highway Bridge Systems—0
Deep Koopman Learning of Nonlinear Time-Varying Systems—0
Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems—0
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels—0
Design Amortization for Bayesian Optimal Experimental Design—0
Efficient Diffusion Models for Vision: A Survey—0
Fast Saturating Gate for Learning Long Time Scales with Recurrent Neural Networks—0
Deep Learning-based Facial Appearance Simulation Driven by Surgically Planned Craniomaxillofacial Bony Movement—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified