Neural Coffee
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A Deep Dive into Deep Learning
Immerse yourself in the exciting world of Deep Learning at Neural Coffee!
Every Friday, we’ll gather to discuss the latest advancements and ideas in the field and expand our knowledge in a relaxed and friendly environment.
All discussions will be held in English.
Open to All, Welcome to All
Neural Coffee is open to anyone who shares a passion for deep learning, regardless of their background or affiliation. Whether you’re a student, staff member, or simply have an interest in Deep Learning, this reading group offers a chance to meet and connect with a community of like-minded individuals. The only requirement is to have basic knowledge of Deep Learning.If you have completed a deep learning course (at the uni or online) and have programmed any neural network architecture from scratch on Tensorflow, Pytorch, or NumPy you are good to go! So come and join us, and be a part of the excitement!
Be Prepared, Be Involved
Take charge of your learning experience and bring a paper, video, or article to share and discuss at each meeting.
Engage in lively discussions and ask questions.
With coffee provided to keep you fueled, the only thing missing is you!
When? Where? Who?
Time: Every Friday 11:00 am – 13:00pm
Location: Seminar Room D, Franz Josef Street 18, 8700 Leoben
Organizer: Fotis Lygerakis, Doctoral Student at the Chair of Cyber-Physical Systems
Questions?
Feel free to address any questions regarding Neural Coffee to fotios.lygerakis@unileoben.ac.at
Not confident with Deep Learning yet?
That’s ok! We will be here for you when you’ve mastered DL. Here is a list of resources that can take you from zero to hero:
Machine Learning
- Introduction to Machine Learning at CPS (University of Leoben)
- Introduction to Machine Learning Lab at CPS (University of Leoben)
- Machine Learning Course in Coursera
- Machine Learning Lectures (Stanford University)
- Machine Learning Lectures (University of Tübingen)
Deep Learning
- Deep Learning Lectures (MIT)
- Deep Learning Lectures (University of Tübingen)
- Deep Learning Course in Coursera
- AI courses
- Introduction to Pytorch
- Introduction to Tensorflow
Meetings Agenda
- 24.02.2023 – Introduction of Neural Coffee Reading Group
- 03.03.2023 – David Ha, Jürgen Schmidhuber, World Models, 2018, NIPS [paper] [article]
- 10.03.2023 – Ian J. Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, et al, Generative Adversarial Nets, 2014, NIPS [paper] [article]
- 17.03.2023
- Jonathan Ho, Ajay Jain, Pieter Abbeel, Denoising Diffusion Probabilistic Models, 2020, NeurIPS. [paper] [article 1] [article 2] [article 2]
- Introduction to Lambda calculus by Dr. Mario Weitzer
- 24.03.2023 Vaswani, A., Shazeer, et al. (2017). Attention is All you Need. In Advances in Neural Information Processing Systems. Curran Associates, Inc. [paper] [article 1] [article 2] [video 1] [video 2]
- 31.03.2023 Geoffrey Hinton (2022). The Forward-Forward Algorithm: Some Preliminary Investigations. Presented at Advances in Neural Information Processing Systems 2022. [paper][article 1][article 2][video 1][video 2]
- 21.04.2023 Li Jing, Pascal Vincent, Yann LeCun, & Yuandong Tian, Understanding Dimensional Collapse in Contrastive Self-supervised Learning. ICLR 2022 [paper] [blog] [video] [code]
- 12.05.2023 Mathilde Caron, Ishan Misra, Julien Mairal, Priya Goyal, Piotr Bojanowski, & Armand Joulin (2020). Unsupervised Learning of Visual Features by Contrasting Cluster Assignments. NeurIPS. 2020 [paper][blog]
Member Book Suggestions
From Bacteria to Bach and Back: The Evolution of Minds, by Daniel C. Dennett, ISBN-10: 0393355500