Patents by Inventor Henry Markram

Henry Markram has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11126911
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.
    Type: Grant
    Filed: August 1, 2019
    Date of Patent: September 21, 2021
    Assignee: Ecole Polytechnique Federale De Lausanne (EPFL)
    Inventors: Henry Markram, Rodrigo de Campos Perin, Thomas K. Berger
  • Publication number: 20210182681
    Abstract: Distance metrics and clustering in recurrent neural networks. For example, a method includes determining whether topological patterns of activity in a collection of topological patterns occur in a recurrent artificial neural network in response to input of first data into the recurrent artificial neural network, and determining a distance between the first data and either second data or a reference based on the topological patterns of activity that are determined to occur in response to the input of the first data.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Henry Markram, Felix Schürmann, Fabien Jonathan Delalondre, Ran Levi, Kathryn Pamela Hess Bellwald, John Rahmon
  • Publication number: 20210182654
    Abstract: Abstracting data that originates from different sensors and transducers using artificial neural networks. A method can include identifying topological patterns of activity in a recurrent artificial neural network and outputting a collection of digits. The topological patterns are responsive to an input, into the recurrent artificial neural network, of first data originating from a first sensor and second data originating from a second sensor. Each topological pattern abstracts a characteristic shared by the first data and the second data. The first and second sensors sense different data. Each digit represents whether one of the topological patterns of activity has been identified in the artificial neural network.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Henry Markram, Felix Schürmann, Fabien Jonathan Delalondre, Daniel Milan Lütgehetmann, John Rahmon
  • Publication number: 20210182653
    Abstract: Application of the output from a recurrent artificial neural network to a variety of different applications. A method can include identifying topological patterns of activity in a recurrent artificial neural network, outputting a collection of digits, and inputting a first digit of the collection to a first application that is designed to fulfil a first purpose and to a second application that is designed to fulfil a second purpose, wherein the first purpose differs from the second purpose. The topological patterns are responsive to an input of data into the recurrent artificial neural network and each topological pattern abstracts a characteristic of the input data. Each digit represents whether one of the topological patterns of activity has been identified in the artificial neural network.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Henry Markram, Felix Schürmann, Fabien Jonathan Delalondre, Daniel Milan Lütgehetmann, John Rahmon
  • Publication number: 20210182657
    Abstract: A method includes defining a plurality of different windows of time in a recurrent artificial neural network, wherein each of the different windows has different durations, has different start times, or has both different durations and different start times, identifying occurrences of topological patterns of activity in the recurrent artificial neural network in the different windows of time, comparing the occurrences of the topological patterns of activity in the different windows, and classifying, based on a result of the comparison, a first decision that is represented by a first topological pattern of activity that occurs in a first of the windows as less robust than a second decision that is represented by a second topological pattern of activity that occurs in a second of the windows.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Henry Markram, Felix Schürmann, John Rahmon, Daniel Milan Lütgehetmann, Constantin Cosmin Atanasoaei
  • Publication number: 20210182655
    Abstract: Robust recurrent artificial neural networks and techniques for improving the robustness of recurrent artificial neural networks. For example, a system can include a plurality of nodes and links arranged in a recurrent neural network, wherein either transmissions of information along the links or decisions at the nodes are non-deterministic, and an output configured to output indications of occurrences of topological patterns of activity in the recurrent artificial neural network.
    Type: Application
    Filed: December 11, 2019
    Publication date: June 17, 2021
    Inventors: Henry Markram, Felix Schürmann, Daniel Milan Lütgehetmann, John Rahmon
  • Patent number: 10799502
    Abstract: Compositions for prevention or treatment of non-inflammatory neuronal damage from brain trauma and strokes are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of non-inflammatory neuronal damage from brain trauma and strokes are also provided, and the methods include administering such compositions.
    Type: Grant
    Filed: March 17, 2017
    Date of Patent: October 13, 2020
    Assignee: Societe des Produits Nestle S.A.
    Inventors: Susana Camacho, Stephanie Michlig Gonzales, Johannes Le Coutre, Henry Markram, Maurizio Pezzoli
  • Publication number: 20200304284
    Abstract: Methods, systems, and devices for homomorphic encryption. In one implementation, the methods include inputting first data into a recurrent artificial neural network, identifying patterns of activity in the recurrent artificial neural network that are responsive to the input of the secure data, storing second data representing whether the identified patterns of activity comports with topological patterns, and statistically analyzing the second data to draw conclusions about the first data.
    Type: Application
    Filed: March 18, 2019
    Publication date: September 24, 2020
    Inventors: Henry Markram, Felix Schuermann, Kathryn Hess, Fabien Delalondre
  • Publication number: 20200304285
    Abstract: Methods, systems, and devices for encrypting and decrypting data. In one implementation, an encryption method includes inputting plaintext into a recurrent artificial neural network, identifying topological structures in patterns of activity in the recurrent artificial neural network, wherein the patterns of activity are responsive to the input of the plaintext, representing the identified topological structures in a binary sequence of length L and implementing a permutation of the set of all binary codewords of length L. The implemented permutation is a function from the set of binary codewords of length L to itself that is injective and surjective.
    Type: Application
    Filed: March 18, 2019
    Publication date: September 24, 2020
    Inventors: Kathryn Hess, Henry Markram
  • Publication number: 20190378008
    Abstract: A method that is implemented by one or more data processing devices can include receiving a training set that includes a plurality of representations of topological structures in patterns of activity in a source neural network and training a neural network using the representations either as an input to the neural network or as a target answer vector. The activity is responsive to an input into the source neural network.
    Type: Application
    Filed: June 11, 2018
    Publication date: December 12, 2019
    Inventors: Henry Markram, Ran Levi, Kathryn Pamela Hess Bellwald, Felix Schuermann
  • Publication number: 20190378007
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for characterizing activity in a recurrent artificial neural network. In one aspect, a method can include characterizing activity in an artificial neural network. The method is performed by data processing apparatus and can include identifying clique patterns of activity of the artificial neural network. The clique patterns of activity can enclose cavities.
    Type: Application
    Filed: June 11, 2018
    Publication date: December 12, 2019
    Inventors: Henry Markram, Ran Levi, Kathryn Pamela Hess Bellwald
  • Publication number: 20190377976
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for characterizing activity in a recurrent artificial neural network. In one aspect, a method for identifying decision moments in a recurrent artificial neural network includes determining a complexity of patterns of activity in the recurrent artificial neural network, wherein the activity is responsive to input into the recurrent artificial neural network, determining a timing of activity having a complexity that is distinguishable from other activity that is responsive to the input, and identifying the decision moment based on the timing of the activity that has the distinguishable complexity.
    Type: Application
    Filed: June 11, 2018
    Publication date: December 12, 2019
    Inventors: Henry Markram, Ran Levi, Kathryn Pamela Hess Bellwald
  • Publication number: 20190378000
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for characterizing activity in a recurrent artificial neural network. In one aspect, a method includes outputting digits from a recurrent artificial neural network, wherein each digit represents whether or not activity within a particular group of nodes in the recurrent artificial neural network comports with a respective pattern of activity.
    Type: Application
    Filed: June 11, 2018
    Publication date: December 12, 2019
    Inventors: Henry Markram, Ran Levi, Kathryn Pamela Hess Bellwald
  • Publication number: 20190377999
    Abstract: In one implementation, a method is implemented by a neural network device and includes inputting a representation of topological structures in patterns of activity in a source neural network, wherein the activity is responsive to an input into the source neural network, processing the representation, and outputting a result of the processing of the representation. The processing is consistent with a training of the neural network to process different such representations of topological structures in patterns of activity in the source neural network.
    Type: Application
    Filed: June 11, 2018
    Publication date: December 12, 2019
    Inventors: Henry Markram, Ran Levi, Kathryn Pamela Hess Bellwald, Felix Schuermann
  • Publication number: 20190354841
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.
    Type: Application
    Filed: August 1, 2019
    Publication date: November 21, 2019
    Inventors: Henry Markram, Rodrigo de Campos Perin, Thomas K. Berger
  • Publication number: 20190307748
    Abstract: Compositions for treatment or prevention of autism disorders are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of autism disorders are also provided, and the methods include administering such compositions.
    Type: Application
    Filed: June 24, 2019
    Publication date: October 10, 2019
    Inventors: Susana Camacho, Stephanie Michlig Gonzalez, Johannes Le Coutre, Henry Markram, Maurizio Pezzoli
  • Patent number: 10387767
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.
    Type: Grant
    Filed: August 3, 2012
    Date of Patent: August 20, 2019
    Assignee: Ecole Polytechnique Federale De Lausanne (EPFL)
    Inventors: Henry Markram, Rodrigo de Campos Perin, Thomas K. Berger
  • Patent number: 10373048
    Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for organizing trained and untrained neural networks. In one aspect, a neural network device includes a collection of node assemblies interconnected by between-assembly links, each node assembly itself comprising a network of nodes interconnected by a plurality of within-assembly links, wherein each of the between-assembly links and the within-assembly links have an associated weight, each weight embodying a strength of connection between the nodes joined by the associated link, the nodes within each assembly being more likely to be connected to other nodes within that assembly than to be connected to nodes within others of the node assemblies.
    Type: Grant
    Filed: August 27, 2015
    Date of Patent: August 6, 2019
    Assignee: Ecole Polytechnique Federale De Lausanne (EPFL)
    Inventors: Henry Markram, Rodrigo de Campos Perin, Thomas K. Berger
  • Patent number: 10369151
    Abstract: Compositions for treatment or prevention of autism disorders are provided, and the compositions contain a therapeutically effective amount of a compound selected from the group consisting of Menthol, Linalool, Icilin and combinations thereof. Methods for treatment or prevention of autism disorders are also provided, and the methods include administering such compositions.
    Type: Grant
    Filed: May 23, 2014
    Date of Patent: August 6, 2019
    Assignee: Societe des Produits Nestle S.A.
    Inventors: Susana Camacho, Stephanie Michlig Gonzalez, Johannes Le Coutre, Henry Markram, Maurizio Pezzoli
  • Publication number: 20180285716
    Abstract: The simplification of neural network models is described. For example, a method for simplifying a neural network model includes providing the neural network model to be simplified, defining a first temporal filter for the conveyance of input from a neuron to an other spatially-extended neuron along the arborized projection, defining a second temporal filter for the conveyance of input from yet another neuron to the spatially-extended neuron along the arborized projection, replacing, in the neural network model, the first, spatially-extended neuron with a first, spatially-constrained neuron and the arborized projection with a first connection extending between the first, spatially-constrained neuron and the second neuron, wherein the first connection filters input from the second neuron in accordance with the first temporal filter and a second connection extending between the first spatially-constrained neuron and the third neuron.
    Type: Application
    Filed: April 2, 2018
    Publication date: October 4, 2018
    Inventors: Henry Markram, Wulfram Gerstner, Marc-Oliver Gewaltig, Christian Rössert, Eilif Benjamin Muller, Christian Pozzorini, Idan Segev, James Gonzalo King, Csaba Erö, Willem Wybo