DSE2023 Summer school and conference theme: Deep Learning for Solving and Estimating Dynamic Models
DSE summer school will equip early and mid-stage PhD students with tools and hands-on computational instruction in deep learning applied to solving and estimating dynamic models, thereby closely integrating economic and econometric theory in empirical work.
The summer school will consist of 4 days of lectures and will run alongside with 2 days conference in dynamic structural econometrics. The conference brings together top junior and senior researchers from the field to discuss recent advances in theoretical and applied work.
This is a past event
You are welcome to browse the lecture schedule and the conference program using the links on the left, as well as browse through the teaching materials available through a public GitHub repository, and videos posted on our YouTube channel.
Tuition fee for the summer school (in-person)
Upon registration the admitted students will have to pay the a small tuition fee:
- PhD students: 250 CHF (about 280 $USD)
- Postdocs/faculty: 400 CHF (about 450 $USD)
There will be a limited amount of hotel rooms available for admitted students (upon a first come first serve basis).
Conference fee (in-person)
For those who only attend the conference, there is a conference fee of 100 CHF (about 110 $USD).
Invited speakers and lecturers
Lecturers of the summer school and invited conference speakers include:
DSE 2023 is grateful for the support from Nuvolos — the collaborative computational workspace for researchers and students alike. With Nuvolos, DSE students will have elastically scalable compute resources ready to hand and can do their work directly in the browser.
We look forward to having you for DSE2023 in Lausanne in August!