Abstract: In some embodiments, an electronic device displays a plurality of content items in a messaging conversation. In some embodiments, the electronic device displays user interfaces associated with one or more content items in a messaging conversation.

Abstract: In some embodiments, an electronic device displays a plurality of content items in a messaging conversation. In some embodiments, the electronic device displays user interfaces associated with one or more content items in a messaging conversation.

Abstract: Techniques are provided for the automated risk assessment of a document. In one embodiment, the techniques involve mapping, via a risk assessment engine, one or more sentences in a first document to one or more risk categories, identifying, via a classification engine, risk-associated language of the one or more sentences based on the one or more risk categories, mapping, via a risk assessment engine, the risk-associated language of the one or more sentences to one or more risk criterion of a risk criterion document, and generating, via a risk assessment engine, a first risk assessment based on the one or more risk criterion of the risk criterion document.

Abstract: To automate time series forecasting machine learning pipeline generation, a data allocation size of time series data may be determined based on one or more characteristics of a time series data set. The time series data may be allocated for use by candidate machine learning pipelines based on the data allocation size. Features for the time series data may be determined and cached by the candidate machine learning pipelines. Predictions of each of the candidate machine learning pipelines using at least the one or more features may be evaluated. A ranked list of machine learning pipelines may be automatically generated from the candidate machine learning pipelines for time series forecasting based upon evaluating predictions of each of the one or more candidate machine learning pipelines.

Abstract: To rank time series forecasting in machine learning pipelines, time series data may be incrementally allocated from a time series data set for testing by candidate machine learning pipelines based on seasonality or a degree of temporal dependence of the time series data. Intermediate evaluation scores may be provided by each of the candidate machine learning pipelines following each time series data allocation. One or more machine learning pipelines may be automatically selected from a ranked list of the one or more candidate machine learning pipelines based on a projected learning curve generated from the intermediate evaluation scores.

Abstract: The present disclosure provides a wavelength conversion structure, a light-emitting apparatus, and a display device using the wavelength conversion structures. The wavelength conversion structure includes a porous inorganic shell and a plurality of organic complex phosphor particles filled in the porous inorganic shell. Wherein the plurality of organic complex phosphor particles is capable of being excited to emit light with a peak wavelength in the visible light range.

Abstract: A method for shielding a system-in-package (SIP) assembly from electromagnetic interference (EMI) includes laminating a pre-form EMI shielding film onto the assembly in a single lamination process. The EMI shielding film may be moldable in a vacuum lamination process to cover the SIP assembly and to substantially fill trenches formed in the assembly between adjacent component modules. The SIP assembly is accordingly shielded from EMI through the application of a single EMI shielding film.

Abstract: Techniques regarding one or more automated machine learning processes that analyze time series data are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that selects a machine learning pipeline for meta transfer learning on time series data by sequentially allocating subsets of training data from the time series data amongst a plurality of machine learning pipeline candidates.

Abstract: Techniques are provided for the automated risk assessment of a document. In one embodiment, the techniques involve mapping, via a risk assessment engine, one or more sentences in a first document to one or more risk categories, identifying, via a classification engine, risk-associated language of the one or more sentences based on the one or more risk categories, mapping, via a risk assessment engine, the risk-associated language of the one or more sentences to one or more risk criterion of a risk criterion document, and generating, via a risk assessment engine, a first risk assessment based on the one or more risk criterion of the risk criterion document.

Abstract: The present invention relates to methods of selecting, screening, engineering, making and modifying antibodies that have improved bioavailability upon subcutaneous administration to a human. Antibodies and variant antibodies with improved bioavailability upon subcutaneous administration to a human are also described.

Abstract: In some embodiments, an electronic device presents representations of messaging conversations. In some embodiments, an electronic device indicates which messages are replies to other messages in a messaging conversation. In some embodiments, an electronic device creates and presents links (e.g., rich links) to contacts in a messaging conversation (e.g., “mentions”). In some embodiments, an electronic device presents indications of messages that are replies to other messages. In some embodiments, an electronic device presents options to create a link (e.g., a rich link) to contacts in a messaging conversation (e.g., “mentions”) using a suggested entry user interface element.

Abstract: In some embodiments, an electronic device presents representations of messaging conversations. In some embodiments, an electronic device indicates which messages are replies to other messages in a messaging conversation. In some embodiments, an electronic device creates and presents links (e.g., rich links) to contacts in a messaging conversation (e.g., “mentions”). In some embodiments, an electronic device presents indications of messages that are replies to other messages. In some embodiments, an electronic device presents options to create a link (e.g., a rich link) to contacts in a messaging conversation (e.g., “mentions”) using a suggested entry user interface element.

Abstract: Techniques regarding multivariate time series data analysis are provided. For example, one or more embodiments described herein can comprise a system, which can comprise a memory that can store computer executable components. The system can also comprise a processor, operably coupled to the memory, and that can execute the computer executable components stored in the memory. The computer executable components can comprise a time series analysis component that generates a machine learning model that discovers a dependency between multivariate time series data using an attention mechanism controlled by an uncertainty measure.

Abstract: In some embodiments, an electronic device presents representations of messaging conversations. In some embodiments, an electronic device indicates which messages are replies to other messages in a messaging conversation. In some embodiments, an electronic device creates and presents links (e.g., rich links) to contacts in a messaging conversation (e.g., “mentions”). In some embodiments, an electronic device presents indications of messages that are replies to other messages. In some embodiments, an electronic device presents options to create a link (e.g., a rich link) to contacts in a messaging conversation (e.g., “mentions”) using a suggested entry user interface element.

Abstract: Embodiments relate to a system, program product, and method for employing deep learning techniques to fused data across modalities. A multi-modal data set is received, including a first data set having a first modality and a second data set having a second modality, with the second modality being different from the first modality. The first and second data sets are processed, including encoding the first data set into one or more first vectors, and encoding the second data set into one or more second vectors. The processed multi-modal data set is analyzed, and the encoded features from the first and second modalities are iteratively and asynchronously fused. The fused modalities include combined vectors from the first and second data sets representing correlated temporal behavior. The fused vectors are then returned as output data.

Abstract: For a plurality of hosts, observe first time-varying characteristics including network throughput, central processing unit (CPU) usage, and/or memory usage; second time-varying characteristics including software configuration; and time-invariant characteristics including hardware configuration, at a plurality of timestamps. Construct a restricted HMM configured to predict actual host states, wherein the first time-varying characteristics include observed variables. The current observed variables depend on current values of the hidden variables and prior timestamp distribution of the observed variables. The former in turn depend on prior timestamp values of the hidden variables, the time-invariant characteristics of the hosts. and current timestamp values of the second time-varying characteristics.

Abstract: Provided herein are conductive formulations which are useful for applying conductive material to a suitable substrate; the resulting coated articles have improved EMI shielding performance relative to articles coated with prior art formulations employing prior art methods. In accordance with certain aspects of the present invention, there are also provided methods for filling a gap in an electronic package to achieve electromagnetic interference (EMI) shielding thereof, as well as the resulting articles shielded thereby. Specifically, invention methods utilize capillary flow to substantially fill any gaps in the coating on the surface of an electronic package. Effective EMI shielding has been demonstrated with very thin coating thickness.

Abstract: A method for shielding a system-in-package (SIP) assembly from electromagnetic interference (EMI) includes laminating a pre-form EMI shielding film onto the assembly in a single lamination process. The EMI shielding film may be moldable in a vacuum lamination process to cover the SIP assembly and to substantially fill trenches formed in the assembly between adjacent component modules. The SIP assembly is accordingly shielded from EMI through the application of a single EMI shielding film.

Abstract: Provided herein are conductive formulations which are useful for applying conductive material to a suitable substrate; the resulting coated articles have improved EMI shielding performance relative to articles coated with prior art formulations employing prior art methods. In accordance with certain aspects of the present invention, there are also provided methods for filling a gap in an electronic package to achieve electromagnetic interference (EMI) shielding thereof, as well as the resulting articles shielded thereby. Specifically, invention methods utilize capillary flow to substantially fill any gaps in the coating on the surface of an electronic package. Effective EMI shielding has been demonstrated with very thin coating thickness.

Abstract: A method for shielding a system-in-package (SIP) assembly from electromagnetic interference (EMI) includes laminating a pre-form EMI shielding film onto the assembly in a single lamination process. The EMI shielding film may be moldable in a vacuum lamination process to cover the SIP assembly and to substantially fill trenches formed in the assembly between adjacent component modules. The SIP assembly is accordingly shielded from EMI through the application of a single EMI shielding film.