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About | DeepCausality

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What is DeepCausality? DeepCausality is a hyper-geometric computational causality library that enables fast and deterministic context aware causal reasoning …

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DeepCausality

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About

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What is DeepCausality? DeepCausality is a hyper-geometric computational causality library that enables fast and deterministic context aware causal reasoning over complex multi-stage causality models. Deep Causality adds only minimal overheads, and thus is suitable for real-time applications without additional acceleration hardware. Examples where DeepCausality can be used include dynamic control systems in the IoT industry, dynamic monitoring systems in the cloud industry, and dynamic market models in the financial industry. Start-ups aiming to disrupt existing industries may also explore DeepCausality to gain a competitive edge.

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What is DeepCausality? DeepCausality is a hyper-geometric computational causality library that enables fast and deterministic context aware causal reasoning over complex multi-stage causality models. Deep Causality adds only minimal overheads, and thus is suitable for real-time applications without additional acceleration hardware. Examples where DeepCausality can be used include dynamic control systems in the IoT industry, dynamic monitoring systems in the cloud industry, and dynamic market models in the financial industry. Start-ups aiming to disrupt existing industries may also explore DeepCausality to gain a competitive edge.

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