Seminar on Machine Intelligence: Brain Decoding and Collaborative Discussions

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The seminar on machine intelligence covered topics like brain decoding for visual perception reconstruction and collaborative group discussions. Participants engaged in analyzing research papers, understanding complex concepts, and exploring implications and limitations of the work. Activities included group discussions and jigsaw collaborative discussions focused on extending the research, proposing new algorithms, and exploring future research questions. The seminar aimed to foster collaboration and innovation in the field of machine intelligence.


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  1. Seminar Maschinelle Intelligenz Lesson 5 14.05.2024 Stefan R hrl, Klaus Diepold, Marisa Ripoll

  2. Selected Reading for Week 5 Brain decoding: toward real-time reconstruction of visual perception Benchetrit, Yohann, Hubert Banville, and Jean-R mi King. "Brain decoding: toward real-time reconstruction of visual perception." arXiv preprint arXiv:2310.19812 (2023) 2

  3. Activity 1: Group Discussion Discuss in Groups the following questions and topics: 1. 2. 3. 4. What did you learn from the paper? Were there some concepts you didn t understand? Can your classmates explain these concepts? Discuss the impact, limitations and implications of this work. Any further open questions related to the paper. Discussion time: 20 Minutes 3

  4. Activity 2: Jigsaw Collaborative Discussion Discussion Guidelines: - - - Each group is given a large paper, some pens and a topic of discussion. The oldest person in the group is selected as the group representative. After 15 minutes everyone except the group representative must stand up and sit at another table (pick a table you haven t sat in before and try mixing with new people don t all stay in the same group the entire activity) Once the new team is seated, the representative explains what the previous group discussed and what conclusions were reached. The new team can then build upon what the previous team did. Once explanations are made and questions are answered, the representatives move to another table and join a new group. A new representative is then chosen and the process repeats. - - - For every Topic answer the following questions: - How can we extend upon this work? - What research questions will follow? - What new algorithms, architectures, pipelines and experimental setups could we use for future work? Topic: 1) Contrastive Learning (!), losses, metrics and algorithms. 2) Brain Module Architecture and ML in Neural Decoding 3) Image Module and Generation Module 4) End-to-end pipeline and general ideas. 4

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