Palantir Technologies Inc.

David Fowler

David Skiff

Christopher Martin

Thomas McArdle

Aravind Baratha Raj

Timothy James Slatcher

Jesse Rickard

Timothy Slatcher

Andrew Floren

Methods and systems for providing a user interface and workflow for interacting with time series data, and applying portions of time series data sets for refining regression models. A system can present a user interface for receiving a first user input selecting a first model from a list of models for modeling the apparatus, generate and display a first chart depicting a first time series data set depicting data from a first sensor, generate and display a second chart depicting a second time series data set depicting a target output of the apparatus, receive a second user input of a portion of the first time series data set, and generate and display a third chart depicting a third time series data set depicting an output of the selected model and aligned with the second chart of the target output and updated in real-time in response to the second user input.

Chart-based time series regression model user interface

Systems, computer program products, and computer-implemented methods for visualizing and interacting with a plurality of models that collectively represent a real world system depicted in a graphical user interface (GUI). The system described herein may generate an interactive GUI with multiple modes and a plurality of panels associated with the plurality of models. These panels and modes lay the framework for how a user can properly visualize and analyze the models at a particular point in time or over a period of time. The systems, computer program products, and computer-implemented methods may thus, according to various embodiments, enable a plurality of models that collectively represent a real world system be interacted with and visualized by a graphical user interface.

Interactive graphical user interfaces for simulated systems

Systems, computer program products, and computer-implemented methods for determining relationships between one or more outputs of a first model and one or more inputs of a second model that collectively represent a real world system, and chaining the models together. For example, the system described herein may determine how to chain a plurality of models by training an artificial intelligence system using the nodes of the models such that the trained artificial intelligence system predicts related output and input node connections. The system may then link related nodes to chain the models together. The systems, computer program products, and computer-implemented methods may thus, according to various embodiments, enable a plurality of discrete models to be optimally chained.

System and method for chaining discrete models

Chart-based time series model user interface

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New York, NY, United States of America

David Fowler