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discussion 2024-07-07

Summary​

In the Discord chat, users engaged in technical discussions primarily focused on advancements in neural networks and machine learning techniques. Shaw shared various GitHub links related to Slot Diffusion models (LSD), intent-slot coattention mechanisms for transforming rules into objects within these models, and KAN networks that utilize spline functions as activations. The conversation also touched on the exploration of polynomial functions over linear summation functions in neural network architectures, with Shaw providing a GitHub link to resources about using polynomial functions like ax^2 + bx + c for activation purposes. Throughout the chat, there were no explicit decisions made or community milestones achieved; however, users actively exchanged knowledge and research materials on cutting-edge topics in artificial intelligence.

FAQ​

  • What are some good papers or resources for using polynomial or sinusoidal functions instead of linear functions in neural networks?

  • Shaw: Shaw provided a link to KAN networks that use splines (a type of polynomial function) for activations, which might be relevant to the questioner's research. They also clarified whether the inquiry was about activation functions or summation functions before activation, suggesting ax^2 + bx + c as an alternative to wx + b.

  • How do KAN networks use splines in their architecture?

    • Shaw: In response to a follow-up question from Chatgpt_down, Shaw provided a link (https://github.com/KindXiaoming/pykan) that presumably contains information on how KAN networks implement spline functions within their neural network structure.

Who Helped Who​

  • Shaw helped Chatgpt_down with understanding polynomial functions in neural networks by providing a link to KAN networks, which use splines for activations. This provided an alternative approach to linear activation functions like ReLU and addressed their interest in using polynomial functions of the form ax^2 + bx + c instead of wx + b.
  • Shaw helped Chatgpt_down with finding relevant research by sharing a GitHub repository related to KAN networks, which could potentially offer insights into implementing polynomial activation functions within neural network models.

Action Items​

  • Technical Tasks
  • Investigate the use of polynomial functions ax^2 + bx + c instead of linear functions wx + b in neural networks (mentioned by Chatgpt_down)
  • Documentation Needs
    • No specific documentation needs were explicitly requested in this chat.
  • Feature Requests
    • Explore the implementation and benefits of KAN networks using splines for activations as an alternative to linear-ish activations like ReLU (mentioned by Shaw)
  • Community Tasks
    • Share and discuss relevant research papers, GitHub repositories, and resources related to neural network architectures, intent-slot coattention models, and polynomial functions in neural networks (led by Shaw and others who shared links).