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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

Showing 1–25 of 37 papers

TitleStatusHype
Dynamic Dual Gating Neural NetworksCode1
Learning Task-Oriented Communication for Edge Inference: An Information Bottleneck ApproachCode1
A Survey on Dynamic Neural Networks: from Computer Vision to Multi-modal Sensor FusionCode1
HADAS: Hardware-Aware Dynamic Neural Architecture Search for Edge Performance ScalingCode1
Temporal Domain Generalization with Drift-Aware Dynamic Neural NetworksCode1
DyFADet: Dynamic Feature Aggregation for Temporal Action DetectionCode1
Dynamic DNNs and Runtime Management for Efficient Inference on Mobile/Embedded DevicesCode1
Dynamic Neural Networks: A Survey—0
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
AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks—0
Analysis of Memory Organization for Dynamic Neural Networks—0
An Introduction to Cognidynamics—0
A Novel Membership Inference Attack against Dynamic Neural Networks by Utilizing Policy Networks Information—0
A Survey on Dynamic Neural Networks for Natural Language Processing—0
Cavs: A Vertex-centric Programming Interface for Dynamic Neural Networks—0
DyCL: Dynamic Neural Network Compilation Via Program Rewriting and Graph Optimization—0
Nimble: Efficiently Compiling Dynamic Neural Networks for Model Inference—0
On-Demand Resource Management for 6G Wireless Networks Using Knowledge-Assisted Dynamic Neural Networks—0
Parametric Taylor series based latent dynamics identification neural networks—0
Siamese Labels Auxiliary Learning—0
Stock Price Prediction using Dynamic Neural Networks—0
Subnetwork-to-go: Elastic Neural Network with Dynamic Training and Customizable Inference—0
The Dark Side of Dynamic Routing Neural Networks: Towards Efficiency Backdoor Injection—0
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