Others
Reading Notes / Resources / Inspirations
Useful Resources
Some research tools, groups, and webpages I often return to:
- Hung-yi Lee – Machine Learning / Deep Learning (YouTube)
- Andrew Ng – Coursera Machine Learning Notes (by fengdu78)
- DailyArXiv
- Papers with Code
- AutoDL
- XianGuYun (仙宫云)
- Prof. Jeff Z. Pan – Knowledge Representation
Inspirations
People and words that remind me why I pursue research:
- “As a woman in a very male-dominated subject, there is no question that challenges remain to achieve gender parity. But this is all the more reason why we women need to keep pursuing our passions in mathematics and nudging those scales towards balance.” - from Dr Sarah Heaps.
I remain deeply grateful for her teaching at Durham, which first introduced me to the foundations of Bayesian statistics.
- I am also thankful to Prof. Camila Caiado and Dr Yi Wang, whose thoughtful guidance gave me clarity and encouragement at a time when I was struggling to choose between PhD offers.