Difference between revisions of "Directed Acyclic Graph (DAG)"
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* [[Data Flow Graph (DFG)]] | * [[Data Flow Graph (DFG)]] | ||
* [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]] | * [[Graph Convolutional Network (GCN), Graph Neural Networks (Graph Nets), Geometric Deep Learning]] | ||
| − | * [[Platforms: Machine Learning as a Service (MLaaS)]] | + | * [[Platforms: AI/Machine Learning as a Service (AIaaS/MLaaS)]] |
* [http://stats.stackexchange.com/questions/234694/can-all-neural-network-with-dag-topology-be-trained-by-back-prop Can all neural network having directed acyclic graph (DAG) topology be trained by back propagation methods? | StackExchange] | * [http://stats.stackexchange.com/questions/234694/can-all-neural-network-with-dag-topology-be-trained-by-back-prop Can all neural network having directed acyclic graph (DAG) topology be trained by back propagation methods? | StackExchange] | ||
Revision as of 09:56, 14 October 2020
YouTube search... ...Google search
- 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
DAG Technology: 'DAG Coins' as an Alternative to Blockchain/Cryptocurrencies
