Rules📜

• All participants must form teams (even if the team is composed of a single participant), and each participant can only be a member of a single team.

• Any individual participating with multiple or duplicate Grand Challenge profiles will be disqualified.

• Anonymous participation is not allowed. To qualify for ranking on the validation/testing leaderboards, true names and affiliations [university, institute (if any) or company (if any), country] must be displayed accurately on verified Grand Challenge profiles, for all participants.

• Members of sponsoring or organizing centers may participate in the challenge but are not eligible for prizes or final ranking in the Closed Testing Phase.

• This is a code execution challenge. Rather than submitting your predicted labels, you'll package everything needed to do inference and submit that for containerized execution.

• All Docker containers submitted to the challenge will be run in an offline setting (i.e. they will not have access to the internet, and cannot download/upload any resources). All necessary resources (e.g. pre-trained weights) must be encapsulated in the submitted containers apriori.

• External data and pre-trained models are allowed in this competition as long as they are freely and publicly available under a permissive open source license . Participants must clearly state the use of external data in their submission, using the algorithm name [e.g. "Biochemical recurrence AI Model (trained w/ external data)"], algorithm page and/or a supporting publication/URL. 
  

• To participate in the Closed Testing Phase, participants submit a short arXiv paper on their methodology (~3 pages) and a public/private URL to their source code on GitHub (hosted with a permissive license). We take these measures to ensure credibility and reproducibility of all proposed solutions, and to promote open-source AI development.

• Participants and their AI algorithms must adhere to the compute limits. It is the responsibility of the participants to ensure their algorithm runtime fits within the compute limits.

• Participants of the LEOPARD challenge, as well as all non-participating researchers using the LEOPARD public training dataset, must adhere to the publication embargo period and can publish their own results, separately only after the completion of the embargo period (after the publication of the LEOPARD challenge journal paper and the publicatication of the LEOPARD challenge baseline journal paper). While doing so, they are requested to cite the challenge publication. 

• Organizers of the LEOPARD challenge reserve the right to disqualify any participant or participating team, at any point in time, on grounds of unfair or dishonest practices.

• All participants reserve the right to drop out of the LEOPARD challenge and forego any further participation. However, they will not be able to retract their prior submissions or any published results till that point in time.

• Competition is open to participants worldwide, except if you are a resident of North Korea, Crimea, so-called Donetsk People's Republic (DNR) or Luhansk People's Republic (LNR), or any other place covered by Financial measures, Restrictions on goods EU sanctions. The aforementioned regulation is in place because of a requirement to conform to EU regulations concerning the provision of resources and transfer of finances (challenge award money, etc...)