The Research Seminar: Advanced Machine Learning is a weekly reading group. The focus is on discussing current research papers and results in machine learning. The target audience is active researchers (postdocs, phd students and advanced master students) in the field who want to discuss and stay up to date with recent developments.
Contact Peter Lippmann (peter.lippmann [at] iwr.uni-heidelberg.de) for further details.
Next Seminar: 05.06.2023 in INF 205, SR 4.300 starting at 1:00pm
Paper to be discussed: will be announced on Friday 02.06.
Recently discussed papers:
22.05.23
How Attentive are Graph Attention Networks?
Shaked Brody, Uri Alon, Eran Yahav
https://arxiv.org/abs/2105.14491
15.05.23
Sparks of Artificial General Intelligence: Early experiments with GPT-4
Sébastien Bubeck, Varun Chandrasekaran, Ronen Eldan et al
https://arxiv.org/abs/2303.12712
08.05.23
Discrete Variational Autoencoders
Jason Tyler Rolfe
https://arxiv.org/abs/1609.02200
24.04.23
Is the Performance of My Deep Network Too Good to Be True? A Direct Approach to Estimating the Bayes Error in Binary Classification
Takashi Ishida, Ikko Yamane, Nontawat Charoenphakdee, Gang Niu, Masashi Sugiyama
https://openreview.net/forum?id=FZdJQgy05rz
17.04.23
Image as Set of Points
Xu Ma, Yuqian Zhou, Huan Wang, Can Qin, Bin Sun, Chang Liu, Yun Fu
https://openreview.net/forum?id=awnvqZja69
03.04.23
Advancing mathematics by guiding human intuition with AI
Davies, A., Veličković, P., Buesing, L., Blackwell, S., Zheng, D., Tomašev, N., ... & Kohli, P
https://www.nature.com/articles/s41586-021-04086-x
27.03.23
DreamFusion: Text-to-3D using 2D Diffusion
Ben Poole, Ajay Jain, Jonathan T. Barron, Ben Mildenhall
https://openreview.net/forum?id=FjNys5c7VyY
20.03.23
Flow Matching for Generative Modeling
Yaron Lipman, Ricky T. Q. Chen, Heli Ben-Hamu, Maximilian Nickel, Matt Le
https://arxiv.org/pdf/2210.02747.pdf