Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting, by a control system for the environment, control settings for the environment based on internal parameters of the control system, wherein: at least some of the control settings for the environment are selected based on a causal model, and the internal parameters include a first set of internal parameters that define a number of previously received performance metric values that are used to generate the causal model for a particular controllable element; obtaining, for each selected control setting, a performance metric value; determining that generating the causal model for the particular controllable element would result in higher system performance; and adjusting, based on the determining, the first set of internal parameters.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes identifying a procedural instance; determining a temporal extent for the procedural instance based on temporal extent parameters for the one or more entities in the procedural instance; selecting control settings for the procedural instance; monitoring environment responses to the control settings that are received for the one or more entities; determining which of the environment responses to attribute to the procedural instance in a causal model; and adjusting, based at least in part on the environment responses that are attributed to the procedural instance, the temporal extent parameters for the one or more entities.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes repeatedly selecting control settings for the environment based on (i) a causal model that identifies causal relationships between possible settings for controllable elements in the environment and environment responses that reflect a performance of the control system in controlling the environment and (ii) current values of a set of internal parameters; and during the repeatedly selecting: monitoring environment responses to the selected control settings; determining, based on the environment responses, an indication that one or more properties of the environment have changed; and in response, modifying the current values of one or more of the internal parameters.

Abstract: Machine learning, or geometric deep learning, applied to various dental processes and 5 solutions. In particular, generative adversarial networks apply machine learning to smile design—finished smile, appliance rendering, scan cleanup, restoration appliance design, crown and bridges design, and virtual debonding. Vertex and edge classification apply machine learning to gum versus teeth detection, teeth type segmentation, and brackets and other orthodontic hardware. Regression applies machine learning to coordinate systems, diagnostics, case complexity, and 0 prediction of treatment duration. Automatic encoders and clustering apply machine learning to grouping of doctors, or technicians, and preferences.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes identifying a procedural instance; determining a temporal extent for the procedural instance based on temporal extent parameters for the one or more entities in the procedural instance; selecting control settings for the procedural instance; monitoring environment responses to the control settings that are received for the one or more entities; determining which of the environment responses to attribute to the procedural instance in a causal model; and adjusting, based at least in part on the environment responses that are attributed to the procedural instance, the temporal extent parameters for the one or more entities.

Abstract: Systems and methods for detecting/identifying novel material samples are provided. A test sample image is processed with a trained transformation function to obtain a transformed matrix. A measure of similarity of the test image based on the transformed matrix is compared to a threshold to determine whether the test sample is novel to a batch of material samples that are provided to train the transformation function.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments.

Abstract: Example techniques of this disclosure are directed determining one or more values that represent a monitoring attribute for one or more body-worn tracking devices (BWTDs). In some instances, the techniques include determining a compliance metric that represents a level of compliance for at least one offender. That is, the compliance metric may be a quantitative value that represents whether a user wearing BWTD is complying with established rules or desired behaviors.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting settings for a treatment of a patient. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for providing a treatment to a patient based on a causal model that measures current causal relationships between input settings and effects of treatments on the patient; ii) receiving a measure of an effect of the treatment on the patient; and iii) adjusting, based on the measure of the effect of the treatment on the patient, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments.

Abstract: A method of optimizing a plurality of control signals used in operating a vehicle is described. The operation has a plurality of associated measurable parameters. The method includes: for each control signal, selecting a plurality of potential optimum values from a predetermined set; operating the vehicle in at least a first sequence of operation iterations, where for each pair of sequential first and second operation iterations in the first sequence of operation iterations, the potential optimum value of one control signal in the first operation iteration is replaced in the second operation iteration with a next potential optimum value of the control signal, while the potential optimum values of the remaining control signals are maintained; for each operation iteration, measuring each parameter in the plurality of measurable parameters; and generating confidence intervals for the control signals to determine causal relationships between the control signals and the measurable parameters.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for designing a clinical trial. In one aspect, the method comprises repeatedly performing the following: i) selecting, from a population of patients, patients for being treated with the treatment using a configuration of input settings, wherein the configuration is selected based on a causal model that measures current causal relationships between input settings and a measure of success of the clinical trial; ii) determining the measure of success of the clinical trial for which patients were selected using the certain configuration of input settings; and iii) adjusting, based on the measure of success of the clinical trial, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of manufacturing a biologic pharmaceutical. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for manufacturing a batch of a biologic pharmaceutical based on a causal model that measures current causal relationships between input settings and a measure of a quality of batches of the biological pharmaceutical; ii) determining a measure of the quality of a batch of the biological pharmaceutical manufactured using the configuration of input settings; and iii) adjusting, based on the measure of the quality of the batch of the biological pharmaceutical, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing operations of a supply chain. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for operating a supply chain, based on a causal model that measures causal relationships between input settings and a measure of success of the supply chain; ii) determining the measure of success of the supply chain operated using the configuration of input settings; and iii) adjusting, based on the measure of success of the supply chain operated using the configuration of input settings, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for controlling operations of one or more healthcare facilities. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for controlling operations of the healthcare facilities based on a causal model that measures current causal relationships between input settings and a measure of success of operations at the healthcare facilities; ii) receiving a measure of success of the operation of the healthcare facilities while controlled using the configuration of input settings; and iii) adjusting, based on the measure of success of the operation of the healthcare facilities while controlled using the configuration of input settings, the causal model.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for optimizing a process of manufacturing a product. In one aspect, the method comprises repeatedly performing the following: i) selecting a configuration of input settings for manufacturing a product, based on a causal model that measures causal relationships between input settings and a measure of a quality of the product; ii) determining the measure of the quality of the product manufactured using the configuration of input settings; and iii) adjusting, based on the measure of the quality of the product manufactured using the configuration of input settings, the causal model.

Abstract: A method of performing a process using a plurality of control signals and resulting in a plurality of measurable outcomes is described. The method includes optimizing the plurality of control signals by at least: receiving a plurality of process constraints; receiving, for each measurable outcome, an optimum range; receiving, for each control signal, a plurality of potential optimum values; iteratively performing the process, where for each process iteration, the value of each control signal is selected from among the plurality of potential optimum values received for the control signal; for each process iteration, measuring each outcome in the plurality of measurable outcomes; and generating confidence intervals for the control signals to determine a causal relationship between the control signals and the measurable outcomes. The method includes performing the process using at least the control signals determined by the causal relationship to causally affect at least one of the measurable outcomes.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments. One of the methods includes identifying a procedural instance; determining a temporal extent for the procedural instance based on temporal extent parameters for the one or more entities in the procedural instance; selecting control settings for the procedural instance; monitoring environment responses to the control settings that are received for the one or more entities; determining which of the environment responses to attribute to the procedural instance in a causal model; and adjusting, based at least in part on the environment responses that are attributed to the procedural instance, the temporal extent parameters for the one or more entities.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining causal models for controlling environments.