FAQ

Q: What does the name “ML Collective” mean?

A: “ML” is short for machine learning, our overall research direction. Our “Collective” is a group of people who simply enjoy working together.

Q: What do you do?

A: We do ML research and show it to the world. This includes producing peer-reviewed scientific papers, articles, blog posts, educational videos, technical demonstrations, software packages, and other products that showcase a unique finding or help further the understanding of a scientific subject. In other words, we're a research group, like those in academia or in corporations with a research division, but not!

We also host an open reading group to help promote accessibility in machine learning research.

Q: What core research directions does ML Collective pursue?

A: Our past work has mostly focused on exposing and understanding model representations, optimization, and training dynamics, and using this understanding to design better models. That said, research directions are driven by individual ML Collective members, who may choose to take things in very different directions!

Q: Who are ML Collective for?

A: We provide a default home for researchers without affiliations, support underrepresented and those from non-traditional backgrounds, and we advocate for established researchers to give back, by expanding and diversifying their collaboration circles. We hope to attract researchers who believe scientific advancements do not need to be profit-driven (and in fact, should inherently be nonprofit), success does not only rely upon quantifiable achievements (but also has to do with the holistic growth of researchers in the community), mentorship should not only come with hierarchy or tenure (instead, we all learn from each other’s expertise), and open collaboration is foundational to both the growth of individuals, and the scientific advancement of the field.

Q: Is ML Collective an affiliation? If I’m a member of ML Collective, can I or do I have to use it on my publications?

A: Yes, members may use ML Collective as an affiliation on papers they publish. You do not have to use it on every paper you publish, but you may, as you prefer.

Q: Can I join if I already have a full-time job?

A: Yes! But you’ll need to make sure that any work you choose to share with the group can in fact be shared as per your organization’s policies.

Q: What can I get out of ML Collective (MLC)?

A: If you are an unaffiliated researcher, MLC can simply be your home — where you find collaborators, project ideas, mentorship and advice, support and assistance. If you are already affiliated, MLC can be a place where you broaden and diversify your collaboration circle, craft your mentorship skill, and give back to the research community.

For example, MLC could be for you if:

  1. You are excited about research but have not yet developed a strong research direction and are looking to join a new project;
  2. You have research ideas you’d like to pursue and are looking for collaborators;
  3. You are working on your own research project in a vacuum and could simply use people to bounce your ideas and results off of;
  4. You simply want to learn more about machine learning and are interested in doing so with a community;
  5. You are interested in seeing how and if research within a non-hierarchical, non-monetized organization could work out, and are happy to be part of the experiment;
  6. You already have a research affiliation, collaborators, and a clear direction, but look to give back to society by offering advice, feedback, and mentorship to MLC members. You can bring others’ projects to the next level by sharing your expertise, and help researchers grow by influencing them with your unique experiences.

Q: Does ML Collective charge a membership fee or pay researchers?

A: No to both. MLC does not collect membership or event participation fees. We're working on being able to accept donations to cover operating expenses.

Q: How does one become a researcher at ML Collective?

A: We’re currently working on a process for members of the broader research community to participate. For general inquiries, you can reach us at hello@mlcollective.org. You can also meet a lot of MLC members at our Deep Learning Classics and Trends reading group, which is open to the public.