Summer school for modern AI methods and their applications in scientific discovery.

We want to answer the questions in AI for Science,

• Why do you need AI for your research?

• Which AI is most suitable for your needs?

• How can you use AI properly for your task?

The school will cover both lectures and hands-on coding sessions, with topics including machine learning basics, generative models, Bayesian and simulation-based inference, foundation models and LLM agents.

The problems include, experiment-to-phenomenology (inference and prediction), computation (generation), theory (auto-workflow and Co-Scientist), etc.

• Supervided and Unsupervised Learning your Data

• Parameter Inference and Dynamical Modeling

• Representation Learning and Generation

• Idea to Paper, AI Scientist, etc.

Tutors:
Yangy-yang Tan(UTokyo),  Jinyang Li(KEK/RIKEN), Victor Kawasaki-Bborruat(EPFL), etc.

• Kenji Fukushima (UTokyo)

• Koji Hashimoto (KyotoU)

• Tetsuo Hatsuda (RIKEN)

• Satoshi Iso (RIKEN/KEK)

• Yoshiyuki Kabashima (UTokyo)

• Leo Speidel (RIKEN)

• Masato Taki (Rikkyo U./RIKEN)

• Akinori Tanaka (RIKEN)

• Yang-yang Tan (UTokyo)

• Lingxiao Wang (RIKEN/UTokyo)*
  lingxiao.wang[change it to at]riken.jp

• Secretary
  Keiko Ueda(RIKEN)
  keiko.ueda[change it to at]riken.jp