Zichen WangDissecting da Vinci: a biologist’s view on researching AIBiological approaches to understanding artificial intelligence (AI)·6 min read·Apr 24, 2023--1--1
Zichen WangAI/ML News in June-July 2022The protein ML mania, the Transformer circuits, Amazon re:MARS, and the next big thing in AI/ML·4 min read·Jul 27, 2022----
Zichen WangInteresting papers I read from ICLR 2022A small collection of notable papers I read from (arguably) the most impact AI/ML venue International Conference on Learning…·8 min read·May 26, 2022--1--1
Zichen WangAI/ML news in March-April 2022DALL·E 2, Google’s 540B language model, ICLR’s blog track, Learning on Graphs Conference, and many more news you may have missed·6 min read·Apr 18, 2022----
Zichen WangAI/ML news in Feb 2022GNN year in review, protein ML in the post AlphaFold2 area, a universal self-supervised learning framework, and many more…·5 min read·Feb 10, 2022----
Zichen WanginTowards Data ScienceInteresting papers I read from NeurIPS2020This year’s NeurIPS conference was hosted online. A lot of the recorded contents, including keynote talks, tutorials and workshops are…·8 min read·Dec 28, 2020----
Zichen WangInteresting papers I read from ICML2020 — Part 2A collection of papers I found interesting from #ICML2020. This is a continuation from Part 1.·4 min read·Jul 27, 2020----
Zichen WanginTowards Data ScienceInteresting papers I read from ICML 2020This year’s International Conference on Machine Learning (ICML) is being hosted virtually online and is a great opportunity for people to…·8 min read·Jul 16, 2020----
Zichen WanginTowards Data ScienceContrasting contrastive loss functionsA comprehensive guide to four contrastive loss functions for contrastive learning·8 min read·May 23, 2020--4--4
Zichen WanginTowards Data ScienceContrastive loss for supervised classificationContrasting cross-entropy loss and contrastive loss·6 min read·Apr 29, 2020--2--2