Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Abstract: A computing network comprising a first layer comprising a first set of oscillators and a second layer comprising a second set of oscillators is provided. The computing network further comprises a plurality of adjustable coupling elements between the oscillators of the first set and a plurality of nonlinear elements. The nonlinear elements are configured to couple output signals of the first layer to the second layer. The computing network further comprises an encoding unit configured to receive input signals, convert the input signals into phase-encoded output signals, and provide the phase-encoded output signals to the first layer.

Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Abstract: Techniques and apparatuses for improved weather forecasting using satellite data are described in this publication. The conventional predictions that are utilized for the generation of weather forecasts are commonly based on large-scale weather formations. Such formations are typically directed to large geographical regions of a state, province, or country, and thus may not be accurate for smaller geographical regions. The disclosed techniques and apparatuses utilize satellite data for a macro-location, and mobile-sensor data from mobile devices within that macro-location, to provide improved macro-location weather forecasting.

Abstract: Embodiments of the invention provide a method comprising creating a structural description for at least one neurosynaptic core circuit. Each core circuit comprises an interconnect network including plural electronic synapses for interconnecting one or more electronic neurons with one or more electronic axons. The structural description defines a desired neuronal activity for the core circuits. The desired neuronal activity is simulated by programming the core circuits with the structural description. The structural description controls routing of neuronal firing events for the core circuits.

Abstract: Neural network processors including a window expander circuit and related methods are provided. The window expander circuit may include a first logic circuit configured to store a set of data elements, corresponding to at least a subset of the input data, into a Q number of logical memories, where each of a P number of data elements of the set of the data elements is stored in each of the Q number of logical memories. The window expander circuit may further include a second logic circuit configured to receive the first set of data elements and additional data elements corresponding to the at least the subset of the input data from the Q number of logical memories and expand the at least the subset of the input data until the at least the subset of the input data is expanded based on a predetermined factor.

Abstract: Disclosed are new data structures and artificial intelligence logic that can be utilized to evaluate the drivers of data presented in visualizations. For example, a processor can translate a specification of a driver to be evaluated with respect to a measure shown in a visualization into narrative analytics, where the narrative analytics are configured to evaluate the driver in the context of a data set for the visualization based on a plurality of data structures and processing logic. In turn, a narrative story can be automatically generated about the evaluated driver (for example, describing an impact that the driver candidate may have had on the subject measure of the visualization).

Abstract: A system and method for reaction rules database correction. The method includes receiving a user-input correction to a first reaction rule in a reaction rules database, and locating a second reaction rule in the reaction rules database that is similar to the first reaction rule. The method also includes calculating a correctness score for the second reaction rule, and determining that the correctness score for the second reaction rule is below a threshold correctness score. Additionally, the method includes presenting, in response to the determining that the correctness score for the second reaction rule is below the threshold correctness score, the second reaction rule to a user, receiving a user-input correction to the second reaction rule, and updating the reaction rules database to include the user-input correction to the second reaction rule.

Abstract: The present invention relates to methods for evaluating and/or predicting the outcome of a clinical condition, such as cancer, metastasis, AIDS, autism, Alzheimer's, and/or Parkinson's disorder. The methods can also be used to monitor and track changes in a patient's DNA and/or RNA during and following a clinical treatment regime. The methods may also be used to evaluate protein and/or metabolite levels that correlate with such clinical conditions. The methods are also of use to ascertain the probability outcome for a patient's particular prognosis.

Abstract: A non-transitory recording medium for recording an interaction scenario display control program, which when executed causes a computer to control according to an input of an interaction scenario having a plurality of branches that is stored in a storage unit which branch is to be selected to display corresponding contents and to store information specifying a selected branch in the storage unit, and to generate and display a display screen on which information indicating which branch of the interaction scenario has been selected and how many times it has been selected is displayed by using letters or illustrations by referring to information stored in the storage unit.

Abstract: Data for layers of a convolutional neural network (CNN) is provided by receiving input data values to be processed in a layer of the CNN and determining addresses in banked memory of a buffer in which the received data values are to be stored based upon format data indicating a format parameter of the input data in the layer and indicating a format parameter of a filter which is to be used to process the input data in the layer. The received input data values are then stored at the determined addresses in the buffer for retrieval for processing in the layer.

Abstract: An information processing device includes, a memory, and a processor coupled to the memory and the processor configured to, acquire a neural network, divide the neural network into divided neural networks, identify, based on input-output characteristics of the divided neural networks, parameters of each of polynomial neural networks corresponding to each of the divided neural networks, and output another neural network generated by linking the identified polynomial neural networks.

Abstract: Methods and systems are described for optimizing a predictive model for mobile network communications based on historical context information. In one aspect, historical context information is collected including at least one of communication environment, communication parameter estimates, mobile device statistics, mobile device transmit settings, base station receiver settings, past network statistics and settings, and adjacent network node information statistics and settings, the historical context information including data from communications of at least one mobile device. A predictive model for network communications is determined based on the historical context information. A communication context for a first mobile device different than the at least one mobile device is determined. The first device is scheduled and/or network parameters are set based on the determined predictive model and communication context.

Abstract: One or more embodiments of a content system provide machine-learned storage location recommendations for storing content items. Specifically, an online content management system can train a machine-learning model to identify a storage pattern from previously stored content items in a plurality of storage locations corresponding to a user account of a user. Training the machine-learning model includes training a plurality of classifiers for the plurality of storage locations. The online content management system uses the classifiers to determine whether a content item is similar to the content items in any of the storage locations, and based on the output of the classifiers, provides graphical elements indicating recommended storage locations within a graphical user interface. The user can select a graphical element to move the content item to the corresponding storage location.

Abstract: The technology disclosed determines one or more field values in a set of field values for a particular field in a fielded dataset that are similar to an input value using six similarity measures. A factor vector is generated per similarity measure and combined to form an input matrix. A convolutional neural network processes the input matrix to generate evaluation vectors. A fully-connected network evaluates the evaluation vectors to generate suggestion scalars for similarity to a particular input value. Thresholding is applied to suggestions scalars to determine one or more suggestion candidates for the particular input value.

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for processing sequences using convolutional neural networks. One of the methods includes, for each of the time steps: providing a current sequence of audio data as input to a convolutional subnetwork, wherein the current sequence comprises the respective audio sample at each time step that precedes the time step in the output sequence, and wherein the convolutional subnetwork is configured to process the current sequence of audio data to generate an alternative representation for the time step; and providing the alternative representation for the time step as input to an output layer, wherein the output layer is configured to: process the alternative representation to generate an output that defines a score distribution over a plurality of possible audio samples for the time step.

Abstract: People represented in multiple images can be recognized using accurate facial similarity metrics, where the accuracy can be further improved using contextual information. A set of models can be trained to process image data, and facial features can be extracted from a face region of an image and passed to the trained models. Resulting feature vectors can be concatenated and the dimensionality reduced to generate a highly accurate feature vector that is representative of the face in the image. The feature vector can be used to locate similar vectors in a multi-dimensional vector space, where similarity can be determined based at least in part upon the distance between the endpoints of those vectors in the vector space. Context information from the image can be used to adjust the similarity determination. Similar vectors can be clustered together such that the faces represented by those images are associated with the same person.

Abstract: The present disclosure relates to systems and methods for automatically optimizing a reporting architecture of an application. In one implementation, a system for automatically optimizing a reporting architecture of an application may include a memory storing instructions and an automata processor configured to execute the instructions. The instructions may include identifying one or more state transition elements in the application; determining if two or more state transition elements have disjoint character sets; grouping two or more state transition elements having disjoint character sets into one or more groups; merging state transition elements included in the one or more groups; and outputting a merged report configured for disambiguation on a second processor.

Abstract: An online system maintains an identity graph having links between different types of user identifying information (e.g., email addresses, phone numbers, user identifiers) describing various users of the online system. Based on information received from various sources describing relationships between different types of user identifying information describing a user, the online system generates confidence values for each link between different types of user identifying information. In some embodiments, a confidence value accounts for an amount of time since information describing a relationship between different types of user identifying information was received from a source.

Abstract: A method of recognizing input data includes determining a feature vector corresponding to an ensemble model from input data, based on the ensemble model, and recognizing the input data based on the feature vector. The ensemble model includes a first model and a second model having a structure that is the same as a structure of the first model.