Version: 2022.05
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G06N 3/00 | Computing arrangements based on biological models [2022-01] |
G06N 3/002 | . | {Biomolecular computers, i.e. using biomolecules, proteins, cells (using DNA G06N 3/123; using neurons G06N 3/061)} [2013-01] |
G06N 3/004 | . | {Artificial life, i.e. computers simulating life} [2013-01] |
G06N 3/006 | . . | {based on simulated virtual individual or collective life forms, e.g. single "avatar", social simulations, virtual worlds or particle swarm optimisation} [2019-01] |
G06N 3/02 | . | using neural network models [2019-01] |
G06N 3/04 | . . | Architectures, e.g. interconnection topology [2013-01] |
G06N 3/0409 | . . . | {Adaptive resonance theory [ART] networks} [2019-01] |
G06N 3/0418 | . . . | {using chaos or fractal principles} [2013-01] |
G06N 3/0427 | . . . | {in combination with an expert system} [2013-01] |
G06N 3/0436 | . . . | {in combination with fuzzy logic} [2013-01] |
G06N 3/0445 | . . . | {Feedback networks, e.g. hopfield nets, associative networks} [2013-01] |
G06N 3/0454 | . . . | {using a combination of multiple neural nets} [2013-01] |
G06N 3/0463 | . . . | {Neocognitrons} [2013-01] |
G06N 3/0472 | . . . | {using probabilistic elements, e.g. p-rams, stochastic processors} [2013-01] |
G06N 3/0481 | . . . | {Non-linear activation functions, e.g. sigmoids, thresholds} [2013-01] |
G06N 3/049 | . . . | {Temporal neural nets, e.g. delay elements, oscillating neurons, pulsed inputs} [2013-01] |
G06N 3/06 | . . | Physical realisation, i.e. hardware implementation of neural networks, neurons or parts of neurons [2013-01] |
G06N 3/061 | . . . | {using biological neurons, e.g. biological neurons connected to an integrated circuit} [2013-01] |
G06N 3/063 | . . . | using electronic means [2013-01] |
G06N 3/067 | . . . | using optical means [2013-01] |
G06N 3/08 | . . | Learning methods [2013-01] |
G06N 3/082 | . . . | {modifying the architecture, e.g. adding or deleting nodes or connections, pruning} [2013-01] |
G06N 3/084 | . . . | {Back-propagation} [2013-01] |
G06N 3/086 | . . . | {using evolutionary programming, e.g. genetic algorithms} [2013-01] |
G06N 3/088 | . . . | {Non-supervised learning, e.g. competitive learning} [2013-01] |
G06N 3/10 | . . | Simulation on general purpose computers [2013-01] |
G06N 3/12 | . | using genetic models [2013-01] |
G06N 5/00 | Computing arrangements using knowledge-based models [2022-01] |
G06N 5/003 | . | {Dynamic search techniques; Heuristics; Dynamic trees; Branch-and-bound} [2019-01] |
G06N 5/02 | . | Knowledge representation [2019-01] |
G06N 5/022 | . . | {Knowledge engineering; Knowledge acquisition} [2019-01] |
G06N 5/025 | . . | {Extracting rules from data} [2019-01] |
G06N 5/027 | . . | {Frames} [2013-01] |
G06N 5/04 | . | Inference methods or devices [2013-01] |
G06N 5/041 | . . | {Abduction} [2013-01] |
G06N 5/042 | . . | {Backward inferencing} [2013-01] |
G06N 5/043 | . . | {Distributed expert systems; Blackboards} [2019-01] |
G06N 5/045 | . . | {Explanation of inference steps} [2013-01] |
G06N 5/046 | . . | {Forward inferencing; Production systems} [2019-01] |
G06N 5/047 | . . . | {Pattern matching networks; RETE networks} [2019-01] |
G06N 5/048 | . . | {Fuzzy inferencing} [2013-01] |
G06N 7/00 | Computing arrangements based on specific mathematical models [2022-01] |
G06N 7/005 | . | {Probabilistic networks} [2013-01] |
G06N 7/02 | . |
G06N 7/023 | . . | {Learning or tuning the parameters of a fuzzy system} [2013-01] |
G06N 7/026 | . . | {Development tools for entering the parameters of a fuzzy system} [2013-01] |
G06N 7/04 | . . | Physical realisation [2013-01] |
G06N 7/043 | . . . | {Analogue or partially analogue implementation} [2013-01] |
G06N 7/046 | . . . | {Implementation by means of a neural network (neural networks using fuzzy logic G06N 3/0436)} [2013-01] |
G06N 7/06 | . . | Simulation on general purpose computers [2013-01] |
G06N 7/08 | . | using chaos models or non-linear system models [2013-01] |
| G06N 10/00 | Quantum computing, i.e. information processing based on quantum-mechanical phenomena [2022-01] WARNING
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| G06N 10/20 | . | Models of quantum computing, e.g. quantum circuits or universal quantum computers [2022-01] WARNING
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| G06N 10/40 | . | Physical realisations or architectures of quantum processors or components for manipulating qubits, e.g. qubit coupling or qubit control [2022-01] WARNING
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| G06N 10/60 | . | Quantum algorithms, e.g. based on quantum optimisation, quantum Fourier or Hadamard transforms [2022-01] WARNING
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| G06N 10/70 | . | Quantum error correction, detection or prevention, e.g. surface codes or magic state distillation [2022-01] WARNING
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| G06N 10/80 | . | Quantum programming, e.g. interfaces, languages or software-development kits for creating or handling programs capable of running on quantum computers; Platforms for simulating or accessing quantum computers, e.g. cloud-based quantum computing [2022-01] WARNING
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G06N 20/00 | Machine learning [2021-08] |
G06N 20/10 | . | using kernel methods, e.g. support vector machines [SVM] [2021-08] |
G06N 20/20 | . | Ensemble learning [2021-08] |
G06N 99/00 | Subject matter not provided for in other groups of this subclass [2013-01] |
G06N 99/007 | . | {Molecular computers, i.e. using inorganic molecules (using biomolecules G06N 3/002)} [2013-01] |