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 genuinely curious people who simply enjoy working together.

Q: What do you do?

A: A few things! First, we perform ML research and show it to the world. This includes producing peer-reviewed papers, articles, blog posts, educational videos, technical demonstrations, software packages, and other products that showcase a unique finding or help further our understanding of machine learning. 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.

Finally, we provide services to the community including draft proofreading before conference deadlines, and grad school application pre-reviewing year round; our members are also often open to chat about career paths, research retrospectives, or anything related to ML/AI research. If you have a draft or application you'd like us to take a look at, or if you'd like to chat about careers or research, drop us a line at hello at mlcollective dot org!

Q: What core research directions does ML Collective pursue?

A: Our past work has mostly focused on exposing and understanding neural network 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 ML researchers without affiliations, support aspiring researchers from underrepresented and non-traditional backgrounds, and we hope to attract established researchers who care deeply about diversity, fairness and equality of the community, eager to give back, and open to produce science in an open, collaborative environment. We hope researchers join with the belief that scientific advancements do not need to be profit-driven (and in fact, should inherently be nonprofit), success does not rely upon quantifiable achievements (but can be about how much one helps others, and enables the holistic progress of the community), mentorship does 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. They do not have to use it on every paper they publish, but they may, as they 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 employer’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 writing grants and 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 at mlcollective dot 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.