The following relates generally to system modeling. Some embodiments described herein learn a representation of the parameter feasibility space that make model parameter tuning easier by constraining the search space, thus enabling physical interpretation of the learned model. They also enable model-based system analytics (controls, diagnosis, prognostics) by providing a system model.

Interpolation logic described herein provides a good approximation to a bicubic interpolation, which is generally smoother than bilinear interpolation, without performing all the calculations normally needed for a bicubic interpolation. This allows an approximation of smooth bicubic interpolation to be performed on devices (e.g. mobile devices) which have limited processing resources. At each of a set of predetermined interpolation positions within an array of data points, a set of predetermined weights represent a bicubic interpolation which can be applied to the data points. For a plurality of the predetermined interpolation positions which surround the sampling position, the corresponding sets of predetermined weights and the data points are used to determine a plurality of surrounding interpolated values which represent results of performing the bicubic interpolation at the surrounding predetermined interpolation positions. A linear interpolation is then performed on the surrounding interpolated values to determine an interpolated value at the sampling position.

The present disclosure discloses a method for obtaining optimal variational parameters of a ground state wavefunction for a Hamiltonian system. The method includes initializing a plurality of variational parameters and sending the variational parameters to a quantum computing portion to output a plurality of measurement results. The method includes transmitting the measurement results to a classical computing portion to update the plurality of variational parameters based on the plurality of measurement results and an update rule, and determining whether a measured energy satisfies a convergence rule. When the measured energy does not satisfy the convergence rule, the method includes sending the plurality of updated variational parameters to the quantum computing portion for a next iteration; and when the measured energy satisfies the convergence rule, the method includes obtaining a plurality of optimal variational parameters for the Hamiltonian system.

A data processing device that makes effective use of a data group containing missing data is provided. A series of learning data containing missing data is acquired, and a representative value of data and a validity ratio representing a proportion of valid data being present are calculated from the series of learning data according to a predefined unit of aggregation. Then, learning of an estimation model is performed so as to minimize an error which is based on a difference between an output resulting from inputting the representative value and the validity ratio to the estimation model, and the representative value. Also, a series of estimation data containing missing data is acquired, and a representative value of data and a validity ratio representing a proportion of valid data being present are calculated from the series of estimation data according to a predefined unit of aggregation. Then, the representative value and the validity ratio are input to the learned estimation model and a feature value is acquired or data estimation is performed for the series of estimation data.

A document data processing apparatus includes a memory and a processor. The memory stores a distributed-representation set including multiple distributed representations corresponding to multiple pieces of data. The processor is configured to modify the distributed-representation set on the basis of multiple data pairs and multiple scores corresponding to the data pairs. The data pairs are subjected to learning. The processor is configured to modify the distributed-representation set in such a manner that, for each of the data pairs, a value indicating a relationship in a modified distributed-representation pair corresponding to the data pair comes close to a score corresponding to the data pair.

Methods and apparatus for providing a representation of an environment, for example, in an XR system, and any suitable computer vision and robotics applications. A representation of an environment may include one or more planar features. The representation of the environment may be provided by jointly optimizing plane parameters of the planar features and sensor poses that the planar features are observed at. The joint optimization may be based on a reduced matrix and a reduced residual vector in lieu of the Jacobian matrix and the original residual vector.

Systems, methods, and data processing tools for processing a multi-dimensional dataset are disclosed. The method includes generating a data object linked to the multi-dimensional dataset. The data object includes a plurality of dimension controls, where each dimension control corresponds to a dimension of the multi-dimensional dataset, and each dimension control is an interactive axis extending radially from a central point. The method further includes displaying the data object in a first configuration, receiving user input manipulating at least one dimension control to change the configuration of the data object from the first configuration to a second configuration, and processing the input to determine an operation associated with the user input. Moreover, the method includes processing the linked multi-dimensional dataset in accordance with the determined operation to generate a display object depicting a dataset corresponding to the second configuration of the data object, and displaying the display object.

According to a disclosed embodiment, data analysis is secured with a microservice architecture and data anonymization in a multitenant application. Tenant data is received by a first microservice in a multitenant application. The tenant data is isolated from other tenant data in the first microservice and stored separately from other tenant data in a tenant database. The tenant data is anonymized in the first microservice and thereafter provided to a second microservice. The second microservice stores the anonymized tenant data in an analytics database. The second microservice, upon request, analyzes anonymized tenant data from a plurality of tenants from the analytics database and provides an analytics result to the first microservice.

Multi-dimensional aggregation using user interface workflow composition is described. Data for a computer implemented process is in a set of related data objects in a data store with each object in the set of related data objects representing an entity modelled in the process. A number of levels for a multi-dimensional aggregation associated with a request is determined where each level of the multi-dimensional aggregation represents a different dimension of data values to be aggregated. Data is aggregated at the levels of aggregation based on the relationships between parent objects and children objects. The data for a final level of aggregation is output to a user interface. The final result includes multiple dimensions of data.

Systems and techniques that facilitate max-cut approximate solution via quantum relaxation are provided. In various embodiments, a system can comprise a receiver component that can access a graph having a set of vertices and a set of edges. In various instances, the system can comprise a rounding component that can compute a max-cut approximate solution for the graph based on a quantum Hamiltonian relaxation of the graph.