Intel Corporation

Corning Incorporated

Xiaoran Fang

Hujun Yin

RongZhen Yang

Shoujiang Ma

Jianguo Wang

Dale Robert Powers

William Peter Addiego

Todd Parrish St Clair

Mark Alan Lewis

Huiqing Wu

Matthew Hayes

Xinfeng Xing

Cai Liu

Danhong Zhong

Thomas Jean Glasson

Roychelle Sheneen Ingram-Ogunwumi

John P Hogan

Mehrzad Malmirchegini

Filtration articles herein exhibit excellent filtration efficiency and pressure drop before and after water durability testing. The articles comprise: a honeycomb filter body; inorganic deposits disposed within the honeycomb filter body at a loading of less than or equal to 20 grams of the inorganic deposits per liter of the honeycomb filter body. The inorganic deposits are comprised of refractory inorganic nanoparticles bound by a high temperature binder comprising one or more inorganic components. At least a portion of the inorganic deposits form a porous inorganic network over portions of inlet walls of the honeycomb filter body.

Methods of making honeycomb bodies having inorganic filtration deposits

Aspects for machine learning-based link adaptation are described. For example, an apparatus can determine k-nearest neighbors (K-NNs) based on training data associated with the sub-band and on the signal to interference and noise ratio (SINR) of the sub-band. In aspects, the apparatus can identify a channel quality indicator (CQI) associated with the lowest error rate for the k-NNs and provide the identified CQI to a base station. In aspects, a neural network (NN) can provide labels for CQIs that indicate probability of choosing a CQI, and the CQI having highest probability will be provided to a base station. In aspects, a covariance matrix based on samples of a communication channel can be provided to a NN to determine a rank indicator (RI) corresponding to the channel, and channel state information associated with the (RI) can be sent to the base station. Other aspects are described.

Machine learning-based link adaptation

A method, system, medium, and article provide neural network loop filtering for video coding with multiple alternative neural networks.

Method and system of neural network loop filtering for video coding

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Xiaoran Fang