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 3481–3490 of 4891 papers

TitleStatusHype
A Temporal-oriented Broadcast ResNet for COVID-19 Detection—0
Dynamic Multimodal FusionCode1
Fast Aquatic Swimmer Optimization with Differentiable Projective Dynamics and Neural Network Hydrodynamic Models—0
Adaptive Divergence-based Non-negative Latent Factor Analysis—0
Meta-Sampler: Almost-Universal yet Task-Oriented Sampling for Point CloudsCode1
On Affine Policies for Wasserstein Distributionally Robust Unit Commitment—0
Surrogate Assisted Evolutionary Multi-objective Optimisation applied to a Pressure Swing Adsorption system—0
Bunched LPCNet2: Efficient Neural Vocoders Covering Devices from Cloud to Edge—0
Straightening skewed markets with an index tracking optimizationless portfolio—0
Embedding Recurrent Layers with Dual-Path Strategy in a Variant of Convolutional Network for Speaker-Independent Speech Separation—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified