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
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!
Feel free to address any questions regarding Neural Coffee to firstname.lastname@example.org
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:
- 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]
- 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, byISBN-10: 0393355500