Thursday, June 2
| 10:45 | Welcome | |
| 11:00-11:45 | Bayesian Inference Using Surrogate Operators | Andrew Stuart |
| 11:45-1:30 | Lunch | Nearby options |
| 1:30-2:15 | Localization Schemes: A Framework for Proving Mixing Bounds for MCMC Sampling Algorithms | Yuansi Chen |
| 2:15-3:00 | Thermal State Sampling for Numerical Linear Algebra | Michael Lindsey |
| 3:00-3:30 | Break | |
| 3:30-4:30 | Discussion Session | |
| 4:30-6:30 | Hosted Reception: Guests and speakers are welcome to join us | Location: Patio of Duke's Devil's Krafhouse |
Friday, June 3
| 9:00-9:45 | Prior-preconditioned Conjugate Gradient Method for Accelerated Gibbs Sampling in "large n & large p" Bayesian Sparse Regression | Akihiko Nishimura |
| 9:45-10:30 | The Proximal Sampler | Sinho Chewi |
| 10:30-11:00 | Break | |
| 11:00-11:45 | Learning High-dimensional Functions for Rare Events Sampling In and Out of Equilibrium | Grant Rotskoff |
| 11:45-1:30 | Hosted Lunch: Guests and speakers are welcome to join us | Penn Pavilion |
| 1:30-2:15 | Sampling Under Symmetry | Nisheeth Vishnoi |
| 2:15-3:00 | How Much Can One Learn a PDE from its Solution Data? | Hongkai Zhao |
| 3:00-3:30 | Break | |
| 3:30-4:30 | Discussion Session | |
Saturday, June 4
| 9:00-9:45 | Identifying Differential Equations with Numerical Methods: Time Evolution, Subspace Pursuit and Weak Form | Sung-Ha Kang |
| 9:45-10:30 | Auto-differentiable Ensemble Kalman Filters | Daniel Sanz-Alonso |
| 10:30-11:00 | Break | Grab-and-go fruit and snacks provided |
| 11:00-11:45 | Transport Maps for Conditional Simulation in High Dimensions | Bamdad Hosseini |
| 11:45-12:30 | Revisiting Least-Squares Formulations for Computational Inverse Problems | Kui Ren |
| 12:30 | Closing Remarks |
