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 3281–3290 of 4891 papers

TitleStatusHype
Latent Temporal Flows for Multivariate Analysis of Wearables Data—0
Deep Koopman Learning of Nonlinear Time-Varying Systems—0
Graph Neural Network Surrogate for Seismic Reliability Analysis of Highway Bridge Systems—0
Mixture of Attention Heads: Selecting Attention Heads Per TokenCode1
Model Cascading: Towards Jointly Improving Efficiency and Accuracy of NLP Systems—0
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels—0
Efficient Diffusion Models for Vision: A Survey—0
Design Amortization for Bayesian Optimal Experimental Design—0
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNNCode1
Learning Signal Temporal Logic through Neural Network for Interpretable ClassificationCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified