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 3811–3820 of 4891 papers

TitleStatusHype
Towards Efficient Graph Convolutional Networks for Point Cloud HandlingCode0
ENOS: Energy-Aware Network Operator Search for Hybrid Digital and Compute-in-Memory DNN Accelerators—0
Deformable Capsules for Object Detection—0
Pyramidal Reservoir Graph Neural NetworkCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
Generalized Nesterov's Acceleration-incorporated Non-negative and Adaptive Latent Factor Analysis—0
A New Parallel Adaptive Clustering and its Application to Streaming Data—0
An Energy-efficient Aerial Backhaul System with Reconfigurable Intelligent Surface—0
CCSNet: a deep learning modeling suite for CO_2 storage—0
"Forget" the Forget Gate: Estimating Anomalies in Videos using Self-contained Long Short-Term Memory Networks—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified