-
公开(公告)号:US20210304066A1
公开(公告)日:2021-09-30
申请号:US16854868
申请日:2020-04-21
发明人: Ryota TOMIOKA , Juliana Patrícia VICENTE FRANCO , Alberto MAGNI , Nuno CLAUDINO PEREIRA LOPES , Siddharth KRISHNA , Renato GOLIN
摘要: A computation graph of a machine learning model is accessed from memory and a constraint solver is used to compute a partition of the computation graph into ordered stages of an execution pipeline. In use, when inference or training of the machine learning model takes place by executing the pipeline, execution cost of the stages are balanced according to the computed partition.
-
公开(公告)号:US20180338147A1
公开(公告)日:2018-11-22
申请号:US15637977
申请日:2017-06-29
IPC分类号: H04N19/149 , G10L15/14
CPC分类号: H04N19/149 , G06F17/30598 , G10L15/144 , H04N19/12 , H04N19/61 , H04N19/94 , H04N19/97
摘要: A data compression apparatus is described which has an encoder configured to receive an input data item and to compress the data item into an encoding comprising a plurality of numerical values. The numerical values are grouped at least according to whether they relate to content of the input data item or style of the input data item. The encoder has been trained using a plurality of groups of training data items grouped according to the content and where training data items within individual ones of the groups vary with respect to the style. The encoder has been trained using a training objective which takes into account the groups.
-
公开(公告)号:US20190297328A1
公开(公告)日:2019-09-26
申请号:US16137519
申请日:2018-09-20
摘要: A data compression apparatus is described which has an encoder configured to receive an input data item and to compress the data item into an encoding comprising a plurality of numerical values. The numerical values are grouped at least according to whether they relate to content of the input data item or style of the input data item. The encoder has been trained using a plurality of groups of training data items grouped according to the content and where training data items within individual ones of the groups vary with respect to the style. The encoder has been trained using a training objective which takes into account the groups.
-
公开(公告)号:US20240249800A1
公开(公告)日:2024-07-25
申请号:US18179621
申请日:2023-03-07
发明人: Leon Immanuel KLEIN , Yue Kwang FOONG , Tor Erlend FJELDE , Bruno Kacper MLODOZENIEC , Marc Manuel Johannes BROCKSCHMIDT , Reinhard Sebastian Bernhard NOWOZIN , Frank NOE , Ryota TOMIOKA
摘要: A computerized method for forecasting a future conformation of a molecular system based on a current conformation of the molecular system comprises (a) receiving the current conformation in a trained machine-learning model that has been previously trained to map a plurality of conformations received to a corresponding plurality of conformations proposed; (b) mapping the current conformation to a proposed conformation via the trained machine-learning model, wherein the proposed conformation is appended to a Markov chain; and (c) returning the proposed conformation as the future conformation.
-
公开(公告)号:US20220222531A1
公开(公告)日:2022-07-14
申请号:US17706586
申请日:2022-03-28
发明人: Ryota TOMIOKA , Matthew Alastair JOHNSON , Daniel Stefan TARLOW , Samuel Alexander WEBSTER , Dimitrios VYTINIOTIS , Alexander Lloyd GAUNT , Maik RIECHERT
摘要: A neural network training apparatus is described which has a network of worker nodes each having a memory storing a subgraph of a neural network to be trained. The apparatus has a control node connected to the network of worker nodes. The control node is configured to send training data instances into the network to trigger parallelized message passing operations which implement a training algorithm which trains the neural network. At least some of the message passing operations asynchronously update parameters of individual subgraphs of the neural network at the individual worker nodes.
-
公开(公告)号:US20180336458A1
公开(公告)日:2018-11-22
申请号:US15599058
申请日:2017-05-18
发明人: Ryota TOMIOKA , Matthew Alastair JOHNSON , Daniel Stefan TARLOW , Samuel Alexander WEBSTER , Dimitrios VYTINIOTIS , Alexander Lloyd GAUNT , Maik RIECHERT
CPC分类号: G06N3/063
摘要: A neural network training apparatus is described which has a network of worker nodes each having a memory storing a subgraph of a neural network to be trained. The apparatus has a control node connected to the network of worker nodes. The control node is configured to send training data instances into the network to trigger parallelized message passing operations which implement a training algorithm which trains the neural network. At least some of the message passing operations asynchronously update parameters of individual subgraphs of the neural network at the individual worker nodes.
-
-
-
-
-