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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 981–990 of 4891 papers

TitleStatusHype
HDKD: Hybrid Data-Efficient Knowledge Distillation Network for Medical Image ClassificationCode0
LYTNet: A Convolutional Neural Network for Real-Time Pedestrian Traffic Lights and Zebra Crossing Recognition for the Visually ImpairedCode0
HDMba: Hyperspectral Remote Sensing Imagery Dehazing with State Space ModelCode0
Hard constraint learning approaches with trainable influence functions for evolutionary equationsCode0
3DDX: Bone Surface Reconstruction from a Single Standard-Geometry Radiograph via Dual-Face Depth EstimationCode0
HDiffTG: A Lightweight Hybrid Diffusion-Transformer-GCN Architecture for 3D Human Pose EstimationCode0
Model Input-Output Configuration Search with Embedded Feature Selection for Sensor Time-series and Image ClassificationCode0
Interaction Measures, Partition Lattices and Kernel Tests for High-Order InteractionsCode0
Causal Customer Churn Analysis with Low-rank Tensor Block Hazard ModelCode0
A New Deep-learning-Based Approach For mRNA Optimization: High Fidelity, Computation Efficiency, and Multiple Optimization FactorsCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified