A New Area Of Machine Learning
Probabilistic Intelligience
PI Probaligence gmbh
Easy to use WepApp
STOCHOS
Deep Infinite Mixture of Gaussian Processes (DIM-GP) is PI’s self-developed machine learning algorithm. A unique combination of neural networks (deep learning) and Gaussian processes is used. It can be used to work on a variety of problems, without expert knowledge and without time-consuming setting of hyperparameters! All of our products are written in Python and are therefore very easy to integrate into existing software platforms and workflows.
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Book a Training
online or on site-
General Introduction to ML
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How you can siginficantly improve your work with STOCHOS
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2 days 4 hours each
DIM-GP
Universal applicability
As long as it is annotated data, STOCHOS can be used to carry out sample- and resource-efficient, expert-independent probabilistic machine learning, using existing data or to plan new samples. It is (almost) irrelevant whether the data comes from experiments or simulations. In addition to this supervised learning (normally used for sensitivity analysis and optimization), STOCHOS is also able to carry out unsupervised learning, for example to carry out predictions of time series in order to then carry out optimal control using reinforcement learning. Since STOCHOS can be used equally on CPU/GPU/TPU and even runs on iOS/Android/Linux Embedded/Microcontroller, “real-time” response times are possible.
STOCHOS can do more than ML. In combination with stochastic analysis and optimization, we can map the entire spectrum of computational intelligence. With our users, a wide range of AI tasks can be solved.
new Feature released
Multi Fidelity
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Famous optimizer
Bayesian Optimization
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See how to use our software for your data
Demo Video
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easy to Use Application
WebApp STOCHOS
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Find out more
We have proven experience in various applications
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