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Run your analysis now →https://eureka.patsnap.com/resources/blog/rd-blog/gaussian-process-regression-kernel-hyperparameter-learning-patent-landscape/ · Patsnap · data cut-off 2026-10-15 · downloaded from the live page
Patent Landscape · AI & Machine LearningGaussian Process Regression Kernel Hyperparameter Learning Patents
204 records and 119 families map filers and IPC classes for Gaussian process kernel hyperparameter learning, with no single top filer.
204
Published Records
119
Simple Patent Families
3%
Families Naming the Largest Filer
29%
In Force at Cut-off
204 published records collapse into 119 simple (DOCDB) families; the difference is the same invention filed in more than one country. ROBERT BOSCH GMBH is named on 3 of the 119 patent families in scope. One patent family can name several filers, so these figures are not slices of a divided whole and do not add up. In force = 60 of 204 records still granted and maintained at the data cut-off; the rest are pending, withdrawn, refused or lapsed.
- No single top filer. Robert Bosch GmbH and The University of Sydney are tied at the top with 3 of 119 simple patent families each.
- A long tail of single-filing entrants. 89 of the 91 listed filers hold 2 or fewer simple patent families each.
- Two IPC subclasses cover most of the field. G06F appears on 52.9% and G06N on 46.2% of the 119 simple patent families in scope.
Published byPatsnap Research··6 min readSourced from Patsnap Eureka
Overview
What this dataset covers
This landscape draws on a search for records that mention a Gaussian process regression or Gaussian process model together with a kernel or covariance term and a hyperparameter or learning term. The search carries no date limit, so the 204 published records and 119 simple patent families reflect everything the string matched, not a chosen time window. Simple patent families de-duplicate the same invention across countries; published records count each publication separately.
The filer list behind this page returns 91 organisations, counted by simple patent family and ranked by volume only. The underlying search engine caps what it returns at 100 entities, so this is not a complete census of every filer, and individual inventors are stripped from the named list even though their filings remain inside every total and share on this page.
Records and families in scope
Ordered by volume only, not by importance or claim strength. Counted in simple (DOCDB) patent families, so one invention filed in several countries counts once. Names come from Patsnap's standardised assignee field as recorded on each document; subsidiaries and group companies are not merged. The icon before each name is read from the name itself (words such as University, Institute or Ltd); the data carries no organisation-type field, so treat it as a reading aid rather than a classification. Filings held by named individuals rather than organisations are removed where they can be identified (9 here); that identification is not exhaustive, so an individually held filing can still appear below. Either way those filings stay inside the totals above. This table shows the top 30 of the 91 filers returned for this search; the data endpoint returns at most 100 entities, so even that 91 is not the complete set of filers. A single family can name more than one filer, so these counts overlap and do not add up to the total.
Source: Patsnap Eureka. Assignee ranking and totals. Derived from one Patsnap search for Gaussian Process Regression Kernel Hyperparameter Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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Data
Filing activity and technology split
The figures below are drawn directly from the search results: a filing-trend series counted in published records, and an IPC composition counted in simple patent families.
Filing trend by earliest filing year
The series runs from 2008 (7 records) through a peak so far of 41 records in 2022, counted by published record and earliest filing year. Records filed from 2022 onward are still filling in as later publications arrive, so the most recent years understate eventual totals, this is a publication-lag effect, not a drop in filing.
Counted in published records by earliest filing year, not de-duplicated into families. A filing is counted in the year it was filed, but it only becomes visible after it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. 2022 onwards are therefore still filling in and are shaded; no growth figure on this page uses them. Because this series counts documents rather than inventions, a rise can mean more inventions or the same inventions filed in more countries; this dataset cannot separate the two. This chart covers 2008-2026 (202 records); the 204 total quoted above includes earlier filings outside the window.
IPC subclass composition
G06F (Electric digital data processing) appears on 63 of 119 simple patent families (52.9%) and G06N (Computing based on AI models) on 55 of 119 (46.2%). Because a single family can carry several IPC classes, these two shares add up to more than 100%, and the chart includes smaller subclasses beyond these two.
Shares are the percentage of the 119 patent families in scope. One patent family can carry several IPC classes, so the shares add up to more than 100%.
Source: Patsnap Eureka. Filing trend and technology composition. Derived from one Patsnap search for Gaussian Process Regression Kernel Hyperparameter Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.
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Example record
Method and system for multiple dataset gaussian process modeling
SYDNEY, THE UNIVERSITY OF
The abstract describes a computerized method that stores two datasets of a quantity of interest, generates a Gaussian process model to compute optimized kernel and noise hyperparameters from them, and then applies that model to perform Gaussian process regression, producing estimates of unknown values by a non-parametric fusion of the two measurement datasets.This is the first record returned under the database default sort order, not a ranking by citations, breadth or date. It illustrates one way the search terms appear in a granted document; it is not presented as representative of the field.
Selected as the first record the search returns under the database default order, then shown in full. It is not ranked by citations, claim breadth or commercial importance, and it is not a judgement about which filing in this space matters most.
Source: Patsnap Eureka. The first record the search returned, shown in full. Derived from one Patsnap search for Gaussian Process Regression Kernel Hyperparameter Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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Reading the filer and technology figures
Three figures from the dataset are worth isolating on their own terms, each counted in the unit stated.
Filer concentration
3 families
top count, shared by 2 filers
Two filers tie at the top of the list
Robert Bosch GmbH and The University of Sydney are each named on 3 of the 119 simple patent families in scope. No single filer in the listed 91 holds more than this count, so the list has two entries at the top rather than one.
Counted in simple patent families.
Long tail
89 of 91
filers at 2 or fewer families
Most listed filers hold very few families
89 of the 91 listed filers are named on 2 or fewer simple patent families each. This describes how spread the filer list is; filer rows are not summed into a combined share anywhere on this page because the rows overlap.
Counted in simple patent families; names are not rolled up to corporate group.
Technology split
52.9% / 46.2%
G06F / G06N share of families
G06F and G06N each cover roughly half the families
G06F (Electric digital data processing) is named on 63 of 119 families and G06N (Computing based on AI models) on 55 of 119. Because one family can carry both classes, these two shares overlap and add to more than 100% together.
Counted in simple patent families; a family can carry several IPC classes.
Legal status
60 of 204
records granted and in force
29% of records were in force at retrieval
60 of the 204 published records (29%) were granted and still in force at the 2026-10-15 retrieval date. The remainder cover a mix of statuses not broken out individually here, and this figure describes status at one point in time rather than any measure of quality.
Counted in published records at the stated retrieval date.
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Eureka can read the same corpus for gaps instead of for coverage: under-claimed branches adjacent to gaussian process regression kernel hyperparameter learning patent landscape, with the prior art for and against each one.
Source: Patsnap Eureka. Derived observations on the same dataset. Derived from one Patsnap search for Gaussian Process Regression Kernel Hyperparameter Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
What's Next
Where to take this next
The figures on this page describe what the search returned. Narrowing or verifying specific claims requires reading the underlying documents directly.
Pull the granted claims on the tied filers
Robert Bosch GmbH and The University of Sydney each hold 3 of the 119 families. A family count says nothing about claim scope, so reading the granted claims is the only way to see what each actually covers.
Explore filer portfolios in EurekaCheck the IPC overlap directly
G06F and G06N together cover a large share of the 119 families, with overlap between them. Eureka can filter to the families that carry both classes at once rather than estimating from the two shares separately.
Run an IPC overlap search in EurekaTrack new publications as they land
Records filed from 2022 onward are still arriving in this dataset due to publication lag. A saved search in Eureka surfaces new filings in this space as they publish rather than relying on a static snapshot.
Set up a monitoring search in EurekaSource: Patsnap Eureka. Suggested next steps. No new data: every figure named here is one of those above. Derived from one Patsnap search for Gaussian Process Regression Kernel Hyperparameter Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
FAQ
Common questions on this landscape
A search for Gaussian process regression or model terms together with kernel or covariance and hyperparameter or learning terms returns 204 published records, which de-duplicate down to 119 simple patent families once the same invention filed in multiple countries is merged. The search carries no date limit, so this count spans everything the string matched rather than a fixed window of years. Because the terms are broad, the set includes both records squarely about kernel learning and some records where the terms appear in a broader context.
There is no single top filer in this dataset: Robert Bosch GmbH and The University of Sydney are both named on 3 of the 119 simple patent families. Below that, 89 of the 91 listed filers hold 2 or fewer families each, so the field looks spread across many organisations rather than concentrated in one. The filer list is ordered by volume alone and does not reflect claim scope, validity or any other measure of strength.
Two IPC subclasses cover most of the 119 families: G06F (Electric digital data processing) at 52.9% and G06N (Computing based on AI models) at 46.2%. Because a family can be classified under several IPC codes, these two shares overlap and add to more than 100% between them. Smaller subclasses also appear in the full IPC breakdown shown on the chart, but they sit at lower shares than these two.
60 of the 204 published records, or 29%, were granted and still in force at the retrieval date of 2026-10-15. This is a snapshot of legal status at one moment, not a measure of how many filings succeeded or failed, and the remaining records cover a mix of pending, lapsed, withdrawn and other statuses that are not broken out individually in this dataset. Legal status changes continuously, so a fresh check against the live register is needed before relying on any single record's standing.
The search returned 18 receiving offices in total. The largest few by published record count are the United States with 66, China with 54, the WIPO PCT route with 25, the European Patent Office with 20, India with 9 and Australia with 7. These figures count each office a record was filed in, so they sum to more than the family total, and they describe where applications were filed rather than where any filer is based.
This page does not report a growth rate for this topic: the dataset is thin enough, and the most recent years incomplete enough due to publication lag, that a computed growth figure would not be reliable. The filing-trend chart shows a peak so far of 41 published records in 2022, with records from 2022 onward still filling in as later publications arrive. Readers should treat the recent years as understated rather than as evidence of a decline.
Answers are grounded in the same dataset. Derived from one Patsnap search for Gaussian Process Regression Kernel Hyperparameter Learning Patent Landscape, covering all matching records regardless of filing date (the search string sets no date limit), retrieved 2026-10-15. Counts cover published records only and move as new filings publish.Run this in Eureka MCP
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How this page was built, and what the numbers do and do not mean
Search. Every figure on this page comes from one Patsnap search, run once and not edited afterwards. This is the exact search string:
TAC:(("gaussian process regression" OR "gaussian process model") AND (kernel OR covariance) AND (hyperparameter OR learn*))Reading the field codes: TAC searches the title, abstract and claims of each record, not the full description. The search string sets no date limit, so the scope is every matching record in the database regardless of when it was filed. It is not restricted to recent years. How this string was built matters for how far the counts can be pushed. It was generated in batch from a topic list rather than hand-crafted for this page, and the result set is not manually screened. A keyword search over title, abstract and claims both over-captures (unrelated filings that happen to use the same words) and under-captures (the same invention written in different words). This page cannot measure either effect, so read every figure here as what this particular string returned, not as what exists in the field.
What is being counted. Two different units appear on this page and they are not interchangeable. The filer list and the technology split are counted in simple (DOCDB) patent families: one invention counts once however many countries it was filed in. The total, the jurisdiction split and the filing-year chart are counted in published records: the same invention counts once per publication. For this search that is 204 records and 119 families. Record counts reward filing in many jurisdictions; family counts do not. Shares are only ever taken against a denominator in the same unit, and each one names it.
Who the filers are. Names come from Patsnap's standardised assignee field, as recorded on the documents themselves. They are not rolled up to corporate group: a parent and its subsidiaries appear as separate entries, and a portfolio acquired from another company stays under the name on the document unless the assignment is reflected there. This list is meant to carry organisations, not people. Filings held by a named individual are identified by matching the assignee against the inventors on the same search, and, for names written in Chinese, Japanese or Korean characters, by the name carrying no organisational suffix; those are removed from the list (9 of them here). Neither test is exhaustive: the inventor list it matches against is itself capped, and a personal name written in Latin script with no organisational wording in it cannot be told apart from a short company name by rule. So an individually held filing can still appear in the list. Those filings stay inside every total and share on this page either way, so the listed entries can add up to less than the total. A record shown in full further down still names its assignee exactly as the patent office records it, including where that is a person: that name is how the record is identified and checked. What is left out of the ranking is people as ranked entries, not people as cited sources. The table shows the top 30 of the 91 filers returned, ordered by count alone; the data endpoint returns at most 100 entities, so even that 91 is not every filer. One patent family can name several filers and each is counted separately, so these rows are not slices of a divided whole: adding them together over-counts, and this page deliberately publishes no combined "top five" share for that reason. See every filer, individuals included
Dates. The year chart counts by earliest filing year, not publication year. A filing only becomes visible once it publishes: roughly 18 months for most routes, and up to 30 months where a PCT application enters national phase. Measured across these pages, the year four back from today still holds only about 89% of its eventual count. 2022 onwards are therefore shaded on the chart as still filling in. The data behind this page was retrieved on 2026-10-15.
Legal status. "In force" counts documents whose legal status at retrieval was granted and maintained (60 of 204). Everything else is pending, withdrawn, refused, lapsed or not determinable, and those states are not broken out here because the underlying codes do not separate them cleanly. Legal status changes continuously and is reported per document, not per family. Get the status breakdown in Eureka
Classification. The technology split uses IPC subclasses (four characters, for example H01M). A single record usually carries several, so the shares add up to more than 100% and a record can appear in more than one bar. Subclass is a coarse grouping; it describes the field a record was classified into, not what the claims cover. Break the classes down to subgroup level
Who wrote the words. The tables, charts, counts, shares and patent numbers on this page are produced directly from the search result by a program; none of them are written or estimated by a language model. The surrounding prose, headings, FAQ answers and the answers in the question panel are drafted by a language model that is given those same figures and is not permitted to introduce others. Prose can still mis-describe a correct figure, so where the two disagree, the tables and charts are the record.
Disclaimer. This page is generated from Patsnap Eureka data drawn from a limited snapshot of global patent and scientific-literature records, and is provided for general information and reference only.
Patent data carries limitations that apply to every figure above. Recent filings are under-counted, because an application is not public until roughly 18 months after filing and database loading adds further delay. The search string defines and constrains everything shown: records that use different terminology, or that sit outside the fields searched, are absent and cannot be counted. Applicant names, classification codes, legal-status codes and citation records are taken as recorded and may contain errors, duplicates, omissions or stale entries. Ordering by volume is not a measure of quality, scope, enforceability or commercial value, and a larger portfolio is not a stronger one. As a result, the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing on this page constitutes an exhaustive prior-art, novelty, freedom-to-operate, validity or infringement search, nor does it constitute legal, financial, investment, or professional advice, and it should not be relied upon as such. No attorney-client relationship is created by it. Any patent, commercial, or strategic decision should be verified independently against the primary records and reviewed with qualified patent, legal, and domain professionals. Patsnap makes no warranties, express or implied, as to the accuracy, completeness, or fitness for any particular purpose of the information presented.
The question panel. The answers behind the suggested questions on this page were written when the page was generated, not in response to your click. The progress steps that play before an answer appears are an animation of how that analysis was done; nothing is being searched or computed at that moment. Typing your own question instead opens Patsnap Eureka, which does run it live.