Program

For talk abstracts see here!

All talks will be held in room 522 on the first floor (same as the reception).

8:45 - 9:30 Sven Wang - Likelihood-Based Methods for Diffusion Data
9:30 - 10:15 Martin Wahl - Upper and Lower Bounds for High-Dimensional Linear Regression Problems
COFFEE BREAK
10:45 - 11:30 Arnulf Jentzen - Convergence Rates for the Adam Optimizer
11:30 - 12:15 Alexander Heinlein - Domain Decomposition for Physics-Informed Neural Networks: Linear and Nonlinear Function Approximation and Operator Learning
LUNCH BREAK
15:00 - 15:30 Anna Shalova - Stationary Measures of Noisy Transformers
15:30 - 16:00 Lea Kunkel - Flow Matching from a KDE Perspective
16:00 - 16:30 Gabriel Clara - On Stochastic Gradient Descent, Algorithmic Noise, and Flatness Regularization
COFFEE BREAK
16:45 - 17:30 Markus Reiß - Early Stopping for Regression Trees
17:30 - 18:15 Mathias Trabs - Uniform Confidence Bands for Centered Purely Random Forests

8:45 - 9:45 Aditya Gilra - Bio-Inspired Learning in Neural Networks: A Tutorial (Part 1)
COFFEE BREAK
10:00 - 10:45 Niklas Dexheimer - Improving the Convergence Rate of Forward Gradient Descent with Repeated Sampling
10:45 - 11:30 Sascha Gaudlitz - Spike-Time Dependent Hebbian Learning as Stochastic Gradient Descent
COFFEE BREAK
11:45 - 12:30 Merle Behr - Interpretability of Random Forest in the Presence of Feature Correlation
LUNCH BREAK
15:30 - 16:15 Jakob Zech - Statistical Learning Theory for Neural Operators
16:15 - 17:00 Michael Kohler - Statistically Guided Deep Learning
COFFEE BREAK
17:15 - 18:00 Claire Boyer - A Primer in Physics-Informed Machine Learning

8:45 - 9:45 Aditya Gilra - Bio-Inspired Learning in Neural Networks: A Tutorial (Part 2)
COFFEE BREAK
10:00 - 10:45 Jiayi Li - Geometry of Neural Networks with Algebraic Activations
10:45 - 11:30 Scott Pesme - Deep Learning Theory through the Lens of Diagonal Linear Networks
COFFEE BREAK
11:45 - 12:30 Kata Vuk - Local Interaction-Based Feature Importance in Tree Ensembles with Applications to Gene Prioritization
LUNCH BREAK
15:30 - 16:15 Botond Szabó - Vecchia Approximation of Deep Gaussian Processes
16:15 - 17:00 Insung Kong - On the Expressivity of Deep Heaviside Networks

8:45 - 9:30 Shayan Hundrieser - New Frontiers in Statistical Optimal Transport
9:30 - 10:15 Matus Telgarsky - TBA
COFFEE BREAK
10:45 - 11:30 Ismael Castillo - Heavy Tails, Adaptation and Benign Overfitting
11:30 - 12:15 Julian Chhor - Benign Overfitting and Adaptive Nonparametric Regression
LUNCH & DEPARTURE

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