Abstract: A device may include a processor. The processor may receive sensor data representative of an environment of a vehicle. The processor may also generate task data using the sensor data in accordance with a perception task. In addition, the task data may include a plurality of features of the environment. The processor may identify a latent representation of a negative effect of the environment within the sensor data. Further, the processor may estimate an error distribution for the task data based on the identified latent representation, the task data, and the perception task. The processor may generate output data. The output data may include a normalized distribution of the plurality of features based on the estimated error distribution and the task data.

Abstract: A localization system includes a first sensor, configured to detect a vibration and generate a first electrical signal in response to the detection of the vibration; a second sensor, configured to detect a vibration and generate a second electrical signal in response to the detection of the vibration; a third sensor, configured to detect a vibration and generate a third electrical signal in response to the detection of the vibration; and a processor, configured to determine a position of a source of the vibration based on the first electrical signal, the second electrical signal, and the third electrical signal.

Abstract: Methods, apparatus, and software for implementing dual Bayesian encoding-decoding for text-to-code transformations. In one aspect, a multi-model probabilistic source code model employing dual Bayesian encoder-decoder models is used to convert natural language (NL) inputs (aka requests) into source code. An NL input is processed to generate a Probabilistic Distribution (PD) of Source code (SC) tokens in an SC token sequence and a PD of Abstract Syntax Tree (AST) tokens in an AST token sequence, wherein each SC token is associated with a respective AST token, and each of the SC and AST tokens have a respective PD. One or more fixing rules are applied to one or more tokens SC tokens that are identified as needing fixing, wherein the fixing rule are selected in consideration of the PDs of the SC tokens and the PDs of their associated AST tokens.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed for object manipulation via action sequence optimization. An example method disclosed herein includes determining an initial state of a scene, generating a first action phase sequence to transform the initial state of the scene to a solution state of the scene by selecting a plurality of action phases based on action phase probabilities, determining whether a first simulated outcome of executing the first action phase sequence satisfies an acceptability criterion and, when the first simulated outcome does not satisfy the acceptability criterion, calculating a first cost function output based on a difference between the first simulated outcome and the solution state of the scene, the first cost function output utilized to generate updated action phase probabilities.

Abstract: Devices and methods for a vehicle are provided in this disclosure. A device for controlling an active seat of a vehicle may include a processor and a memory. The memory may be configured to store a transfer function. The processor may be configured to predict an acceleration of the active seat of the vehicle based on a first sensor data and the transfer function. The first sensor data may include information indicating an acceleration of a vibration source for the vehicle. The processor may be further configured to generate a control signal to control a movement of the active seat at a first instance of time based on the predicted acceleration.

Abstract: An autonomous vehicle (AV) system may include a memory having computer-readable instructions stored thereon. The AV system may include a processor operatively coupled to the memory and configured to read and execute the computer-readable instructions to perform or control performance of operations. The operations may include receive an instruction text vector representative of a command for an AV provided by a user. The operations may include receive an environment text vector representative of a spatio-temporal feature of an environment of the AV. The operations may include generate a sense set that includes words based on the instruction text vector and the environment text vector. The operations may include compare the words of the sense set to navigational instructions (NIs) within a corpus and identify a NI that corresponds to the words based on the comparison. The operations may also include update a trajectory of the AV based on the NI.

Abstract: A human-robot collaboration system, including at least one processor; and a non-transitory computer-readable storage medium including instructions that, when executed by the at least one processor, cause the at least one processor to: predict a human atomic action based on a probability density function of possible human atomic actions for performing a predefined task; and plan a motion of the robot based on the predicted human atomic action.

Abstract: Technologies for management of data layers in a heterogeneous geographic information system (GIS) map are disclosed. A compute device may maintain a GIS database that includes geo-quads that represent physical locations of various scales. Data layers and layer tracks may be dynamically added to the GIS database at different scales, allowing for an extensible framework that enables a mechanism for integrating additional functionality. In the illustrative embodiment, a graph database is used to store the GIS database, allowing for a flexible structure. In some embodiments, entries in layer tracks may include binary large objects that may have properties and associated methods, allowing for application-specific functionality.

Abstract: Methods and apparatus to automatically generate code for graphical user interfaces are disclosed. An example apparatus includes a textual description analyzer to encode a user-provided textual description of a GUI design using a first neural network. The example apparatus further includes a DSL statement generator to generate a DSL statement with a second neural network. The DSL statement is to define a visual element of the GUI design. The DSL statement is generated based on at least one of the encoded textual description or a user-provided image representative of the GUI design. The example apparatus further includes a rendering tool to render a mockup of the GUI design based on the DSL statement.

Abstract: Methods, apparatus, systems, and articles of manufacture are disclosed to identify and interpret code. An example apparatus includes a natural language (NL) processor to process NL features to identify a keyword, an entity, and an intent of an NL string included in an input retrieved from a user; a database driver to transmit a query to a database including an ontological representation of a version control system, wherein the query is a parameterized semantic query including the keyword, the entity, and the intent of the NL string; and an application programming interface (API) to present to the user a code snippet determined based on the query, the code snippet being at least one of uncommented or non-self-documented.

Abstract: Technologies for thermal enhanced semantic segmentation include a computing device having a visible light camera and an infrared camera. The computing device receives a visible light image of a scene from the visible light camera and an infrared image of the scene from the infrared camera. The computing device registers the infrared image to the visible light image to generate a registered image. Registering the infrared image may include increasing resolution of the infrared image. The computing device generates a thermal boundary saliency image based on the registered infrared image. The computing device may generate the thermal boundary saliency image by applying a Gabor jet convolution to the registered infrared image. The computing device performs semantic segmentation on the visible light image, the registered infrared image, and the thermal boundary saliency image to generate a pixelwise semantic classification of the scene. Other embodiments are described and claimed.

Abstract: A system, article, and method of interactive storytelling generates probability-based personalized views factoring observable user behaviors.

Abstract: Systems and methods for determining a configuration for a microarchitecture are described herein. An example system includes a proposal generator to generate a first candidate configuration of parameters for the microarchitecture, a machine learning model to process the first candidate configuration of parameters to output estimated performance indicators for the microarchitecture, an uncertainty checker to determine whether the estimated performance indicators are reliable, and a performance checker. In response to a determination that the estimated performance indicators are reliable, the performance checker is to determine whether the estimated performance indicators have improved toward a target. Further, if the estimated performance indicators have improved, the performance checker is to store the first candidate configuration of parameters in a memory as a potential solution for a microarchitecture without performing a full simulation on the first candidate configuration of parameters.

Abstract: Methods, apparatus, systems and articles of manufacture are disclosed to implement a neural network. An apparatus to implement a neural network, the apparatus comprising memory formed on a substrate, neural network inference logic formed on the same substrate as the memory, the neural network inference logic to load a plurality of neural network parameters in a multiply-accumulate register, and perform a sample-multiply-add operation on the neural network parameter values and input data to generate a neural network inference result, and a memory controller to transfer the neural network inference result to at least one of a host memory external to the substrate or a host processor external to the substrate.

Abstract: Various aspects are related to a map representation system including one or more processors configured to: obtain operation task data, the operation task data indicating one or more operation tasks associated with an operation of one or more autonomous agents within a corresponding operating space; and obtain operation task specific map data as a function of the operation task data, the operation task specific map data representing the operating space corresponding to the one or more operation tasks.

Abstract: A vehicle control system (VCS) for a vehicle may include an in-vehicle bus and an intrusion detection system (IDS). The IDS may: calculate a planned output of the vehicle based on a message of a message stream received from at least one electronic control unit (ECU) coupled to the in-vehicle bus, calculate a reachable set based on an uncertainty metric, and identify an intrusion of the VCS based on a comparison of the planned output and the reachable set.

Abstract: An annotation device may receive 4D sensor data representative of a first scene and that includes a point representative of a human limb in the first scene. The annotation device may also receive 4D data representative of a second scene that includes points representative of a feature in the second scene. In addition, the annotation device may generate a first tree data structure representative of occupation by the human limb in the first scene based on the point and a second tree data structure representative of occupation of the second scene based on the plurality of points. The annotation device may map the first tree data structure and the second tree data structure to a reference frame. The annotation device may determine whether a tree-to-tree structure intersection of the feature and the human limb exists within the reference frame and may annotate the feature based on the tree-to-tree structure intersection.

Abstract: Systems and techniques for locating a radio transmission source by scene reconstruction are described herein. A multipath radio signal—comprised of two or more multipath components—may be received at an antenna array. A collection of angle-of-arrival (AoA) values may be created from the multipath components. Thus, each AoA in the collection corresponds to one of the multipath components. An optical image of the environment may be obtained and possible reflective surfaces for the multipath components identified in the optical image. A set of paths may be created in a model of the environment by backtracking from the antenna array along the AoAs in the collection of AoA values. Here, the backtracking simulates reflections of the ray off of the surfaces identified in the optical image. A transmitter of the multipath radio signal may then be located via the set of paths.

Abstract: A computer-implemented method may include obtaining, from a system using a middleware component of the system, run-time evidence of the system; applying the obtained run-time evidence to a Directed Acyclic Graph (DAG) Bayesian network to determine marginal probabilities for one or more nodes of the DAG Bayesian network, wherein the DAG Bayesian network comprises a plurality of nodes each representing states and faults of the system, wherein each node includes a parameterized conditional probability distribution, and wherein one or more of the nodes of the plurality of nodes specify a list of one or more safety goals and a safety value; determining which nodes representing faults have probabilities exceeding their specified safety value; and determining one or more risk mitigation techniques to activate for the determined nodes representing faults with probabilities exceeding their respective safety value.

Abstract: A method for creating a road user spatio-temporal representation or threat map includes obtaining electronic map data for a spatial region and a plurality of map layers. Creating a map layer includes setting parameter(s) for a vehicle with respect to the map layer. For each subsection of the spatial region, creating the map layer includes defining a position and heading for the vehicle for each of the respective subsections and representing at least one object in the respective subsection using one or more probabilistic distributions with respect to at least velocity and position of the at least one object, and determining a collision risk value between the ego vehicle and the at least one object. The threat map is generated from the map layers with maximum acceptable collision risk values from the map layers.