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Dynamic neural networks

Dynamic neural networks are adaptable models that can change their structure or parameters during training or inference based on input complexity or computational constraints. They offer benefits like improved efficiency, adaptability, and scalability compared to static architectures.

Papers

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Showing 1–25 of 37 papers

TitleStatusHype
Dynamic DNNs and Runtime Management for Efficient Inference on Mobile/Embedded DevicesCode1
DyFADet: Dynamic Feature Aggregation for Temporal Action DetectionCode1
Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck ApproachCode1
HADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance ScalingCode1
Dynamic Dual Gating Neural NetworksCode1
A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor FusionCode1
Temporal Domain Generalization with Drift-Aware Dynamic Neural NetworksCode1
AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural NetworksCode0
Boosted Dynamic Neural NetworksCode0
Dynamic Neural Network is All You Need: Understanding the Robustness of Dynamic Mechanisms in Neural NetworksCode0
DYNASHARE: DYNAMIC NEURAL NETWORKS FOR MULTI-TASK LEARNINGCode0
Fixing Overconfidence in Dynamic Neural NetworksCode0
Jointly-Learned Exit and Inference for a Dynamic Neural Network : JEI-DNNCode0
Nonlinear Systems Identification Using Deep Dynamic Neural NetworksCode0
SATBench: Benchmarking the speed-accuracy tradeoff in object recognition by humans and dynamic neural networksCode0
ED-Batch: Efficient Automatic Batching of Dynamic Neural Networks via Learned Finite State Machines—0
Embedded Knowledge Distillation in Depth-Level Dynamic Neural Network—0
Evolving Artificial Neural Networks To Imitate Human Behaviour In Shinobi III : Return of the Ninja Master—0
Stock Price Prediction using Dynamic Neural Networks—0
Interpretable PID Parameter Tuning for Control Engineering using General Dynamic Neural Networks: An Extensive Comparison—0
GradMDM: Adversarial Attack on Dynamic Networks—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
Subnetwork-to-go: Elastic Neural Network with Dynamic Training and Customizable Inference—0
An Introduction to Cognidynamics—0
Long-Distance Gesture Recognition using Dynamic Neural Networks—0
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