Core Probabilistic Inference Engine
RxInfer is a powerful open-source probabilistic programming framework enabling organizations to make data-driven decisions with quantified uncertainty. Unlike traditional machine learning that gives you just an answer, RxInfer tells you how confident it is in that answer. It forms the core technology upon which advanced solutions by Lazy Dynamics are built.
Implement advanced Bayesian inference with RxInfer. Its elegant API makes complex probabilistic models accessible.
# Instantiate the client from rxinfer import RxInfer client = RxInfer("api-key")# Create a model from a collection of models model = client.models.create_model_instance({ "model_name": "drone-v1", })# Run real-time probabilistic inference result = client.models.run_inference(model.instance_id, { "data": { "observation": get_sensor_data(), } })# Learn from the data client.models.run_learning(model.instance_id, { "parameters": [ "mass", "inertia" ] })
Initialize the client with your API key
Select and configure your model
Run real-time inference
Enable continuous learning
Optimized for performance and scalability
Below is a benchmark comparison between RxInfer's message passing algorithm and Hamiltonian Monte Carlo (HMC) on a linear dynamical system. The benchmark measures time to convergence for inferring the posterior distribution. As shown, on this problem RxInfer's optimized message passing achieves 300x faster inference results compared to traditional HMC sampling.
Optimized message passing with industry-leading performance
Process data with minimal latency for time-critical applications
Optimized CPU and memory utilization reduces operational costs
See why RxInfer is a leading choice over conventional machine learning approaches for complex scenarios.
| Capability | RxInferAdvanced | Traditional MLBasic |
|---|---|---|
| Uncertainty Quantification | Complete probabilistic approach | Point estimates only |
| Adaptability | Continuous online learning | Static models |
| Interpretability | Transparent model reasoning | Black-box predictions |
| Data Efficiency | Works with limited data | Requires large datasets |
RxInfer's advanced probabilistic models deliver more accurate and robust predictions in complex environments.
Develop and deploy models in a fraction of the time required by traditional machine learning approaches.
Significantly reduce operational costs through more efficient algorithms and reduced computational requirements.
RxInfer is a cutting-edge probabilistic programming framework. It harnesses the power of reactive message passing to transform complex data into actionable insights with measurable confidence levels. This foundational technology drives better business outcomes across diverse industries.
Industry-leading capabilities for demanding environments
Explore advanced models and applications built with or facilitated by RxInfer, showcasing its versatility.
Stay ahead of evolving conditions with our adaptive learning system. Models continuously update to ensure predictions maintain accuracy as real-world situations change.
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Let AI design your neural networks. Our automated search technology builds optimized models specifically tailored to your unique data patterns and business requirements.
Tackle complex differential equations with confidence. Our Bayesian approach delivers not just solutions, but comprehensive uncertainty quantification for every calculation.
Master dynamic systems with our sophisticated probabilistic framework. Generate real-time insights and predictions for complex, continuously evolving scenarios.
Dive deeper into the capabilities of RxInfer and see how it can revolutionize your data-driven applications.
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