Directed Acyclic Graph (DAG)

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• Multi-scale recognition with DAG-CNNs | Songfan Yang & Deva Ramanan
• The Key to Building Data Pipelines for Machine Learning: Support for Multiple Engines | Jorge Villamariona - Qubole
• Running Arbitrary DAG-based Workflows in the Cloud | Sachin Tilloo
• Data Flow Graph (DFG)
• Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning
• Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)
• Can all neural network having directed acyclic graph (DAG) topology be trained by back propagation methods? | StackExchange

A DAG network is a neural network for deep learning with layers arranged as a directed acyclic graph. A DAG network can have a more complex architecture in which layers have inputs from multiple layers and outputs to multiple layers. DAGNetwork | MathWorks

DAG workflow are set of tasks written with dependencies between the tasks rather than linearly chaining. 4 Reasons Why Your Machine Learning Code is Probably Bad - Norman Niemer - KDnuggets

• • Example Usage For a Machine Learning Workflow | GitHub

DAG Technology: 'DAG Coins' as an Alternative to Blockchain/Cryptocurrencies

• Decentralized: Federated & Distributed: Blockchain