Korea Advanced Institute of Science and Technology

Samsung Electronics Co., Ltd.

International Business Machines Corporation

Jinwoo Shin

Naoki Abe

Seungwoo Seo

Sungju Hwang

Dongsu Han

Eunho Yang

Kimberly C Lang

Jaehong Kim

Youngbum Hur

Jihoon Tack

Hyunho Yeo

Youyoung Song

Youngmok Jung

A method of training a retrosynthesis prediction model includes determining first attention information from first character string information of a product, based on first graph information of the product, encoding the first character string information, based on the determined first attention information, and determining second attention information from the first graph information and second graph information of a reactant. The method further includes decoding second character string information of the reactant, based on the determined second attention information, and training the retrosynthesis prediction model, based on the decoded second character string information.

Method and apparatus for training retrosynthesis prediction model

A processor-implemented method with image analysis includes: receiving a test image; generating a plurality of augmented images by augmenting the test image; determining classification prediction values for the augmented images using a classifier; determining a detection score based on the classification prediction values; and determining whether the test image corresponds to anomaly data based on the detection score and a threshold.

Method and apparatus with image analysis

A method and apparatus for transmitting adaptive video in real time using a content-aware neural network are disclosed. At least one embodiment provides a method performed by a server for transmitting an adaptive video in real time by using content-aware deep neural networks (DNNs), including downloading a video, encoding a downloaded video for each of at least one resolution, dividing an encoded video into video chunks of a predetermined size, training the content-aware DNNs by using encoded video, generating a configuration or manifest file containing information on trained content-aware DNNs and information on the encoded video, and transmitting the configuration file upon a request of a client.

Method and apparatus for transmitting adaptive video in real time using content-aware neural network

A method for anomaly alarm consolidation includes detecting a plurality of anomalies in time-series data received from an information technology infrastructure; identifying a plurality of root-cause candidates for each of the anomalies; generating, by a scenario analysis of the anomalies, a plurality of alarms, wherein the scenario analysis predicts a plurality of future expected values of the time-series data over a plurality of historical values of the time-series data using a graphical Granger causal model and generates the alarms based on a difference between the future expected values of the time-series data and actual values of the anomalies in the time-series data; and performing a belief propagation procedure between the root-cause candidates and the alarms to determine a plurality of root-causes that collectively comprise attributed root-causes for the alarms.

Consolidating anomaly root causes and alarms using graphical granger models

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Daejeon, South Korea

Jinwoo Shin