Grants and Contributions
About this information
In June 2016, as part of the Open Government Action Plan, the Treasury Board of Canada Secretariat (TBS) committed to increasing the transparency and usefulness of grants and contribution data and subsequently launched the Guidelines on the Reporting of Grants and Contributions Awards, effective April 1, 2018.
The rules and principles governing government grants and contributions are outlined in the Treasury Board Policy on Transfer Payments. Transfer payments are transfers of money, goods, services or assets made from an appropriation to individuals, organizations or other levels of government, without the federal government directly receiving goods or services in return, but which may require the recipient to provide a report or other information subsequent to receiving payment. These expenditures are reported in the Public Accounts of Canada. The major types of transfer payments are grants, contributions and \'other transfer payments\'.
Included in this category, but not to be reported under proactive disclosure of awards, are (1) transfers to other levels of government such as Equalization payments as well as Canada Health and Social Transfer payments. (2) Grants and contributions reallocated or otherwise redistributed by the recipient to third parties; and (3) information that would normally be withheld under the Access to Information Act and the Privacy Act.
$4,500.00
Aug 10, 2017
Machine-learning-assisted, robot-integrated rehabilitation following disability
URU
$4,500.00
Aug 10, 2017
Application of Machine Learning Techniques to Physical Design
URU
$25,000.00
Nov 8, 2017
Improving Static Code Analysis Using Machine Learning Methods
EGP
$4,500.00
Oct 18, 2017
Machine Learning for Data Extraction from Unstructured Documents
USRAI
$4,500.00
Aug 10, 2017
Machine Learning of Parameters for a Tensegrity Structure
URU
$355,000.00
May 10, 2017
Probabilistic methods in computer science and machine learning
RGPIN
$97,712.00
Sep 23, 2021
Academia
Unlocking deep learning capabilities for mineral prospectivity mapping with novel geoscience data augmentation techniques
GC-130021S
The objective of this project is to develop leading edge geophysical and geological data augmentation tools (Artificial Intelligence and machine learning) to improve the practicality of deep learning methods applied to mineral prospectivity mapping, particularly focusing on the Southern Glennie Domain in Saskatchewan to produce mineral prospectivity maps of gold occurrences and electromagnetic anomalies.
$425,000.00
Jun 6, 2022
For-profit organization
Develop next generation mapping tools
992826
Mapping Hub will be a complete redo of the existing Mappedin CMS with a focus on ease-of-use, self-serve onboarding and use of Machine Learning to increase the efficiency of creating and maintaining indoor maps.
$50,000.00
Sep 16, 2019
For-profit organization
ARP - Feasibility - Development of CRISPR assay & data used for machine learning
934801
This data will be used to train machine learning algorithms for the detection and prediction of on/off target effects in CRISPR-Cas assays.
$415,000.00
Aug 1, 2019
For-profit organization
Artificial Intelligence Platform for R&D Tax and Financial Back-office Management
932414
Development of an integrated platform utilizing Machine Learning and Natural Language Processing algorithms to help businesses automate R&D tax claims and other complicated and time-consuming accounting and finance tasks and deliver real-time business insights.