Summer school review.

This summer school offers a captivating program featuring lectures encompassing cutting-edge research topics, ranging from learning phenomena in high-dimensional settings to Wasserstein gradient flow and Mean Field Dynamics of neural networks. Distinguished speakers present their latest works, igniting a sense of exploration among the audience. Engaging in active participation through questions and discussions, the participants foster an exceptional research-oriented atmosphere. One particular highlight is the evening poster sessions, where young researchers present and peruse research findings. The diverse backgrounds of the participants provide a comprehensive perspective on state-of-the-art research in modern machine learning. Moreover, the provision of complimentary breakfasts and lunches by the organizers extends beyond monetary savings. These culinary offerings facilitate dynamic exchanges of ideas among students with varied backgrounds and expertise, fostering stronger bonds and connections among young researchers. The logistical arrangements and organization of the summer school are flawlessly executed. Clear signage on campus and provided accommodations ensure a seamless experience, allowing participants to fully concentrate on their studies and discussions. From the captivating lectures to the enlightening poster sessions, and from the delectable cuisine to the stimulating conversations, this summer school is truly remarkable. I wholeheartedly recommend it to all PhD students specializing in machine learning.

Topics

• Dynamical Mean Field Theory
• Wasserstein Gradient Flow
• High-Dimensional Deep Learning
• Neural Tangent Kernel and Feature Learning
• Replica Method

Extras

• two Poster Sessions + finger foods and drinks
• free breakfast and lunch every day

Rating

• Theory: ★★★★★
• Practice: ★☆☆☆☆
• Interaction: ★★★★★
• Logistics: ★★★★★