Objective
Deep machine learning is revolutionizing computer science. Instead of manually creating complex software, engineers now use automatically generated deep neural networks (DNNs) in critical financial, medical and transportation systems, obtaining previously unimaginable results.
Despite their remarkable achievements, DNNs remain opaque. We do not understand their decision making and cannot prove their correctness - thus risking potentially devastating outcomes. For example, it has been shown that DNNs that navigate autonomous aircraft with the goal of avoiding collisions could produce incorrect turning advisories. Thus, the lack of formal guarantees regarding DNN behavior is preventing their safe deployment in critical systems, and could jeopardize human lives. Consequently, there is a crucial need to ensure that DNNs operate correctly.
Recent and exciting developments in formal verification allow us to automatically reason about DNNs. However, this is a nascent technology, which currently only scales to medium-sized DNNs - whereas real-world systems are much larger. Additionally, it is unclear how to apply this technology in practice. I propose to bridge this crucial gap through the development of novel, scalable and groundbreaking techniques for verifying the correctness of large DNNs, and by applying them to real systems of interest. I will do this by (1) developing search-space pruning techniques, which will enable us to verify larger DNNs; (2) creating novel abstraction-refinement techniques, which will allow us to scale to even larger DNNs; and (3) identifying new kinds of relevant specifications and key domains where DNNs are used, demonstrating the verification of real-world DNNs.
This project will result in a sound and expressive framework for automatically reasoning about DNNs, orders of magnitude larger than is possible today. This framework will ensure the safety and correctness of DNNs deployed in critical systems, greatly benefiting users and society.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences software
- engineering and technology mechanical engineering vehicle engineering aerospace engineering aircraft
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2023-STG
See all projects funded under this callHost institution
Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
91904 JERUSALEM
Israel
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.