This week was the International Conference on Artificial Intelligence and Statistics (AISTATS). A total of 492 papers were presented (44 orals and 448 posters).
I found it very interesting to learn about many different aspects of deep learning and discover new application areas. Many of the papers were quite theoretical and contained a lot of math compared to most of the papers that I usually read, which are more application oriented. There were many papers about Bayesian methods and Gaussian processes of which I apparently don’t know much.
I particularly liked the efforts made by the organizers to support underrepresented groups or new students on their path to ML research. There were mentoring sessions and discussions with people who benefited from affinity groups in other venues. It was enlightening to hear about different perspectives on the accessibility of the research community.
I also presented our paper “Point Cloud Generation with Continuous Conditioning” in the poster session on Monday. You can take a look at the poster below or simply check our project page.