WO2019217835A1 - Training of photonic neural networks through in situ backpropagation - Google Patents
Training of photonic neural networks through in situ backpropagation Download PDFInfo
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- WO2019217835A1 WO2019217835A1 PCT/US2019/031747 US2019031747W WO2019217835A1 WO 2019217835 A1 WO2019217835 A1 WO 2019217835A1 US 2019031747 W US2019031747 W US 2019031747W WO 2019217835 A1 WO2019217835 A1 WO 2019217835A1
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- 230000001537 neural Effects 0.000 title claims abstract description 34
- 238000011065 in-situ storage Methods 0.000 title description 10
- 230000003287 optical Effects 0.000 claims abstract description 15
- 230000004913 activation Effects 0.000 claims description 48
- 230000000306 recurrent Effects 0.000 claims description 5
- XUIMIQQOPSSXEZ-UHFFFAOYSA-N silicon Chemical compound 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- G02B6/293—Optical coupling means having data bus means, i.e. plural waveguides interconnected and providing an inherently bidirectional system by mixing and splitting signals with wavelength selective means
- G02B6/29346—Optical coupling means having data bus means, i.e. plural waveguides interconnected and providing an inherently bidirectional system by mixing and splitting signals with wavelength selective means operating by wave or beam interference
- G02B6/2935—Mach-Zehnder configuration, i.e. comprising separate splitting and combining means
- G02B6/29352—Mach-Zehnder configuration, i.e. comprising separate splitting and combining means in a light guide
- G02B6/29355—Cascade arrangement of interferometers
-
- G—PHYSICS
- G02—OPTICS
- G02F—OPTICAL DEVICES OR ARRANGEMENTS FOR THE CONTROL OF LIGHT BY MODIFICATION OF THE OPTICAL PROPERTIES OF THE MEDIA OF THE ELEMENTS INVOLVED THEREIN; NON-LINEAR OPTICS; FREQUENCY-CHANGING OF LIGHT; OPTICAL LOGIC ELEMENTS; OPTICAL ANALOGUE/DIGITAL CONVERTERS
- G02F1/00—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics
- G02F1/01—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour
- G02F1/21—Devices or arrangements for the control of the intensity, colour, phase, polarisation or direction of light arriving from an independent light source, e.g. switching, gating or modulating; Non-linear optics for the control of the intensity, phase, polarisation or colour by interference
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Computing arrangements based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/0454—Architectures, e.g. interconnection topology using a combination of multiple neural nets
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Computing arrangements based on biological models using neural network models
- G06N3/04—Architectures, e.g. interconnection topology
- G06N3/0481—Non-linear activation functions, e.g. sigmoids, thresholds
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N3/00—Computing arrangements based on biological models
- G06N3/02—Computing arrangements based on biological models using neural network models
- G06N3/08—Learning methods
- G06N3/082—Learning methods modifying the architecture, e.g. adding or deleting nodes or connections, pruning
Abstract
Description
Claims
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EP19799982.4A EP3791332A4 (en) | 2018-05-10 | 2019-05-10 | Training of photonic neural networks through in situ backpropagation |
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Cited By (6)
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US10608663B2 (en) | 2018-06-04 | 2020-03-31 | Lightmatter, Inc. | Real-number photonic encoding |
US10763974B2 (en) | 2018-05-15 | 2020-09-01 | Lightmatter, Inc. | Photonic processing systems and methods |
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US11093215B2 (en) | 2019-11-22 | 2021-08-17 | Lightmatter, Inc. | Linear photonic processors and related methods |
US11209856B2 (en) | 2019-02-25 | 2021-12-28 | Lightmatter, Inc. | Path-number-balanced universal photonic network |
WO2022020437A1 (en) * | 2020-07-21 | 2022-01-27 | The Trustees Of The University Of Pennsylvania | Photonic-electronic deep neural networks |
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- 2019-05-10 JP JP2020562696A patent/JP2021523461A/en active Pending
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Also Published As
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KR20210006962A (en) | 2021-01-19 |
EP3791332A1 (en) | 2021-03-17 |
JP2021523461A (en) | 2021-09-02 |
US20210192342A1 (en) | 2021-06-24 |
EP3791332A4 (en) | 2022-03-09 |
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