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 751–775 of 4891 papers

TitleStatusHype
CSWin-UNet: Transformer UNet with Cross-Shaped Windows for Medical Image SegmentationCode1
ARNN: Attentive Recurrent Neural Network for Multi-channel EEG Signals to Identify Epileptic SeizuresCode1
Corner Proposal Network for Anchor-free, Two-stage Object DetectionCode1
Continual Learning For On-Device Environmental Sound ClassificationCode1
Contrast-Phys+: Unsupervised and Weakly-supervised Video-based Remote Physiological Measurement via Spatiotemporal ContrastCode1
Output Space Entropy Search Framework for Multi-Objective Bayesian OptimizationCode1
Correlation Filters for Unmanned Aerial Vehicle-Based Aerial Tracking: A Review and Experimental EvaluationCode1
PAGE: Prototype-Based Model-Level Explanations for Graph Neural NetworksCode1
Cluster-GCN: An Efficient Algorithm for Training Deep and Large Graph Convolutional NetworksCode1
DAM: Dynamic Attention Mask for Long-Context Large Language Model Inference AccelerationCode1
PATS: Process-Level Adaptive Thinking Mode SwitchingCode1
A framework for data-driven solution and parameter estimation of PDEs using conditional generative adversarial networksCode1
Consistent Accelerated Inference via Confident Adaptive TransformersCode1
PointNorm: Dual Normalization is All You Need for Point Cloud AnalysisCode1
Learning From Alarms: A Robust Learning Approach for Accurate Photoplethysmography-Based Atrial Fibrillation Detection using Eight Million Samples Labeled with Imprecise Arrhythmia AlarmsCode1
Cloth-Changing Person Re-identification from A Single Image with Gait Prediction and RegularizationCode1
A Reverse Mamba Attention Network for Pathological Liver SegmentationCode1
PrimeK-Net: Multi-scale Spectral Learning via Group Prime-Kernel Convolutional Neural Networks for Single Channel Speech EnhancementCode1
Efficient Learning of Mesh-Based Physical Simulation with BSMS-GNNCode1
Privacy-Preserving Graph-Based Machine Learning with Fully Homomorphic Encryption for Collaborative Anti-Money LaunderingCode1
CondenseNet V2: Sparse Feature Reactivation for Deep NetworksCode1
Confronting Ambiguity in 6D Object Pose Estimation via Score-Based Diffusion on SE(3)Code1
PROTO: Iterative Policy Regularized Offline-to-Online Reinforcement LearningCode1
ProtoOcc: Accurate, Efficient 3D Occupancy Prediction Using Dual Branch Encoder-Prototype Query DecoderCode1
Content-aware Token Sharing for Efficient Semantic Segmentation with Vision TransformersCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1ViTaLHamming Loss0.05—Unverified