Reading Group Uncertainty Quantification
The reading group meets every other week to discuss current research papers on the topic Uncertainty Quantification. The discussion is lead by a moderator. Everybody is welcome to attend. Subscription to the group's mailing list is possible here.
Important information: We meet and discuss ONLINE using Zoom. The moderator creates a meeting link and password, and distributes it via the group mailing list.
Winter term 2022/23
| Date | Time | Moderator | Topic |
|---|---|---|---|
| 21.03.23 | 16:00 | Jonas Latz (Edinburgh) | Can Physics-Informed Neural Networks beat the Finite element Method? |
| 20.12.22 | 16:00 | Leila Taghizadeh (TUM) | A-Optimal Active Learning |
| 06.12.22 | 16:00 | Anastasia Istratuca (Edinburgh) | Effective Generation of Compressed Stationary Gaussian Fields |
| 29.11.22 | 16:00 | Elisabeth Ullmann (TUM) | Global sensitivity analysis using derivative-based sparse Poincaré chaos expansions |
| Date | Time | Moderator | Topic | ||
|---|---|---|---|---|---|
| 05.07.22 | 16:00 | Laura Scarabosio (Radboud) | Data driven gradient flows | ||
| 21.06.22 | 16:00 | Daniel Walter (Linz) | Sparse solutions in optimal control of PDEs with uncertain parameters: the linear case | ||
| 07.06.22 | 16:00 | Abdul-Lateef Haji-Ali (Heriot-Watt, Edinburgh) | Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC | ||
| 24.05.22 | 16:00 | Giovanni Rabitti (Heriot-Watt, Edinburgh) | On Shapley Value for Measuring Importance of Dependent Inputs | ||
| 10.05.22 | 16:00 | Florian Beiser (NTNU) | Combining data assimilation and machine learning to infer unresolved scale parametrization |
| Date | Time | Moderator | Topic | ||
|---|---|---|---|---|---|
| 08.02.22 | 16:00 | Felipe Uribe (DTU, Copenhagen) | Unbiased Markov chain Monte Carlo with couplings | ||
| 25.01.22 | 16:00 | Björn Sprungk (Freiberg) | Analysis of a class of Multi-Level Markov Chain Monte Carlo algorithms based on Independent Metropolis-Hastings | ||
| 11.01.22 | 16:00 | Jonas Latz (Heriot-Watt, Edinburgh) | Probability, Frequency and Reasonable Expectation | ||
| 07.12.21 | 16:00 | Leila Taghizadeh (TUM) | Optimal experimental design under irreducible uncertainty for linear inverse problems governed by PDEs | ||
| 23.11.21 | 16:00 | Fabian Wagner (TUM) | Physics-Informed Machine Learning with Conditional Karhunen-Loève Expansions | ||
| 09.11.21 | 16:00 | Elisabeth Ullmann (TUM) | Unbiased MLMC-based variational Bayes for likelihood-free inference | ||
| 26.10.21 | 16:00 | Simon Urbainczyk (Heriot-Watt, Edinburgh) | Analysis of boundary effects on PDE-based sampling of Whittle-Matérn random fields | ||
| 12.10.21 | 16:00 | Jan Stanczuk (Cambridge) | Score-Based Generative Modeling through Stochastic Differential Equations |
| Date | Time | Moderator | Topic | ||
|---|---|---|---|---|---|
| 20.07.21 | 16:00 | Simon Weißmann (Heidelberg) | Consensus Based Sampling | ||
| 06.07.21 | 16:00 | Laura Scarabosio (Radboud) | Estimates on the generalization error of physics-informed neural networks for approximating a class of inverse problems for PDEs | ||
| 22.06.21 | 16:00 | Fabian Wagner (TUM) | Complete dynamics and spectral decomposition of the Ensemble Kalman Inversion | ||
| 08.06.21 | 16:00 | Jonas Latz (Cambridge) | A dynamical systems framework for intermittent data assimilation | ||
| 25.05.21 | 16:00 | Daniel Schaden (TUM) | On quantitative stability in infinite-dimensional optimization under uncertainty | ||
| 11.05.21 | 16:00 | Sam Power (Bristol) | Transport map accelerated Markov chain Monte Carlo | ||
| 27.04.21 | 16:00 | Philipp Eisenhauer (Bonn) | Structural models for policy-making: Coping with parametric uncertainty |
| Date | Time | Moderator | Topic | ||
|---|---|---|---|---|---|
| 09.02.21 | 16:00 | Felipe Uribe (DTU, Copenhagen) | A Stochastic Newton MCMC Method for Large-Scale Statistical Inverse Problems with Application to Seismic Inversion | ||
| 15.12.20 | 16:00 | Jonas Latz (Cambridge) | The linear conditional expectation in Hilbert space | ||
| 01.12.20 | 16:00 | Melina Freitag (Potsdam) | Uncertainty quantification in large Bayesian linear inverse problems using Krylov subspace methods | ||
| 17.11.20 | 16:00 | Elisabeth Ullmann (TUM) | Robust Training and Initialization of Deep Neural Networks: An Adaptive Basis Viewpoint | ||
| 03.11.20 | 16:00 | Fabian Wagner (TUM) | Interacting Langevin Diffusions: Gradient Structure And Ensemble Kalman Sampler | ||
| 20.10.20 | 16:00 | Laura Scarabosio (Radboud) | Bayesian mesh adaptation for distributed parameters |
| Date | Time | Moderator | Topic | ||
|---|---|---|---|---|---|
| 07.07.20 | 16:00 | Simon Weißmann (Mannheim) | Tikhonov Regularization Within Ensemble Kalman Inversion | ||
| 23.06.20 | 16:00 | Florian Beiser (TUM) | Risk-Averse PDE-Constrained Optimization Using the Conditional Value-At-Risk | ||
| 09.06.20 | 16:00 | Robert Scheichl (Heidelberg) | On the geometry of Stein variational gradient descent | ||
| 26.05.20 | 16:00 | Daniel Schaden (TUM) | Continuous Level Monte Carlo and Sample-Adaptive Model Hierarchies | ||
| 12.05.20 | 16:00 | Felipe Uribe (DTU, Copenhagen) | Cauchy difference priors for edge-preserving Bayesian inversion | ||
| 28.04.20 | 16:00 | Jonas Latz (Cambridge) | Calibrate, Emulate, Sample |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 28.01.20 | 16:00 | 02.10.011 | Fabian Wagner | Stein Variational Gradient Descent: A General Purpose Bayesian Inference Algorithm | ||
| 14.01.20 | 16:45 | 02.10.011 | Simon Urbainczyk | Adaptive Sampling Strategies for Stochastic Optimization | ||
| 17.12.19 | 16:00 | 02.10.011 | Ustim Khristenko | Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification | ||
| 19.11.19 | 16:00 | 02.10.011 | Mario Parente | The Lipschitz matrix: a tool for parameter space dimension reduction | ||
| 05.11.19 | 16:00 | 02.10.011 | Fabian Wagner | Estimation of small failure probabilities in high dimensions by subset simulation | ||
| 22.10.19 | 16:00 | 02.10.011 | Jonas Latz | Why Are Big Data Matrices Approximately Low Rank? |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 30.07.19 | 16:00 | 02.10.011 | Yannik Schälte (ICB) | ABC Samplers | ||
| 16.07.19 | 16:00 | 02.10.011 | Brendan Keith (M2) | Optimization of PDEs with uncertain inputs | ||
| 25.06.19 | 16:00 | 02.10.011 | Florian Beiser (M2) | A stochastic gradient method with mesh refinement for PDE constrained optimization under uncertainty | ||
| 18.06.19 | 16:00 | 02.10.011 | Mario Parente (M2) | A transport-based multifidelity preconditioner for Markov chain Monte Carlo | ||
| 28.05.19 | 16:00 | 02.10.011 | Laura Scarabosio (M2) | A Multiscale Strategy for Bayesian Inference Using Transport Maps | ||
| 14.05.19 | 16:15 | 02.10.011 | Elisabeth Ullmann (M2) | Conditional Karhunen-Loeve expansion for uncertainty quantification and active learning in partial differential equation models | ||
| 30.04.19 | 16:15 | 02.10.011 | Ionut-Gabriel Farcas (I5) | Sensitivity-driven adaptive sparse stochastic approximations in plasma microinstability analysis |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 19.02.19 | 16:15 | 02.10.011 | Konstantin Riedl (TUM) | Multifidelity Preconditioning of the Cross-Entropy Method for Rare Event Simulation and Failure Probability Estimation | ||
| 05.02.19 | 16:15 | 02.10.011 | Jonas Latz (M2) | How Deep are Deep Gaussian processes? | ||
| 22.01.19 | 16:15 | 02.10.011 | Fabian Wagner (M2) | Physics-Informed Generative Adversarial Networks for Stochastic Differential Equations | ||
| 08.01.19 | 16:15 | 02.10.011 | Steven Mattis (M2) | A Fast and Scalable Method for A-Optimal Design of Experiments for Infinite-dimensional Bayesian Nonlinear Inverse Problems | ||
| 20.11.18 | 16:15 | 02.10.011 | Ustim Khristenko (M2) | Analysis of boundary effects on PDE-based sampling of Whittle-Matérn random fields | ||
| 06.11.18 | 16:15 | 02.10.011 | Laura Scarabosio (M2) | Well-posed Bayesian geometric inverse problems arising in subsurface flow | ||
| 23.10.18 | 16:15 | 02.10.011 | Mario Parente (M2) | A probabilistic framework for approximating functions in the active subspace |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 24.07.18 | 16:15 | 02.10.011 | Sabrina Balzer (M2) | Posterior Consistency for Gaussian Process Approximations of Bayesian Posterior Distributions | ||
| 10.07.18 | 16:15 | 02.10.011 | Mario Parente (M2) | Importance Sampling and Necessary Sample Size: An Information Theory Approach | ||
| 26.06.18 | 16:15 | 02.10.011 | Daniel Schaden (M2) | MCMC Methods for Functions: Modifying Old Algorithms to Make Them Faster | ||
| 12.06.18 | 16:15 | 02.10.011 | Ludger Pähler (TUM) | PDE-Net: Learning PDEs from Data | ||
| 29.05.18 | 16:15 | 02.10.011 | Elisabeth Ullmann (M2) | Efficient white noise sampling and coupling for multilevel Monte Carlo with non-nested meshes | ||
| 15.05.18 | 16:15 | 02.10.011 | Jonas Latz (M2) | Deep Learning: An Introduction for Applied Mathematicians | ||
| 24.04.18 | 16:15 | 02.10.011 | Steven Mattis (M2) | Combining Push-Forward Measures and Bayes' Rule to Construct Consistent Solutions to Stochastic Inverse Problems |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 30.01.18 | 16:15 | 02.10.011 | Elisabeth Ullmann (M2) | Machine learning of differential equations using Gaussian processes (Paper 1) (Paper 2) | ||
| 16.01.18 | 16:15 | 02.10.011 | Jonas Latz (M2) | Statistical analysis of differential equations: introducing probability measures on numerical solutions | ||
| 05.12.17 | 16:15 | 02.10.011 | Steven Mattis (M2) | A Short Course on Duality, Adjoint Operators, Green’s Functions, and A Posteriori Error Analysis (§3-4) | ||
| 21.11.17 | 16:15 | 02.10.011 | Steven Mattis (M2) | A Short Course on Duality, Adjoint Operators, Green’s Functions, and A Posteriori Error Analysis (§1-2) | ||
| 07.11.17 | 16:15 | 02.10.011 | Laura Scarabosio (M2) | Finite element methods for semilinear elliptic stochastic partial differential equations | ||
| 24.10.17 | 16:15 | 02.10.011 | Piotr Swierczynski (M2) | An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 12.04.17 | 14:00 | 02.08.011 | Laura Scarabosio (M2) | A Fresh Look at the Kalman Filter | ||
| 02.05.17 | 16:15 | 03.06.011 | Mario Parente (M2) | Ensemble Kalman methods for inverse problems | ||
| 16.05.17 | 16:15 | 03.06.011 | Ionut Farcas (CS) | An efficient Bayesian inference approach to inverse problems based on an adaptive sparse grid collocation method | ||
| 06.06.17 | 16:15 | 03.06.011 | Jonas Latz (M2) | Analysis of the ensemble Kalman filter for inverse problems | ||
| 27.06.17 | 16:15 | 03.06.011 | Elisabeth Ullmann (M2) | On the Brittleness of Bayesian Inference | ||
| 11.07.17 | 16:15 | 03.06.011 | Mario Parente (M2) | Active Subspaces: Emerging Ideas for Dimension Reduction in Parameter Studies (§1-3) | ||
| 25.07.17 | 16:15 | 03.06.011 | Steven Mattis (M2) | Active Subspaces: Emerging Ideas for Dimension Reduction in Parameter Studies (§4-6) | ||
| 23.08.17 | 10:00 | 03.06.011 | Daniel Schaden (M2) | Optimal Model Management for Multifidelity Monte Carlo Estimation |
| Date | Time | Room | Moderator | Topic | ||
|---|---|---|---|---|---|---|
| 17.11.16 | 10:00 | 03.11.018 | Jonas Latz (M2) | Stuart - Uncertainty Quantification in Bayesian Inversion | ||
| 08.12.16 | 10:15 | 03.11.018 | Elisabeth Ullmann (M2) | Stuart(2010) - Inverse Problems: A Bayesian Perspective (§6) | ||
| 15.12.16 | 10:15 | 03.11.018 | Elisabeth Ullmann (M2) | Stuart(2010) - Inverse Problems: A Bayesian Perspective (§6) | ||
| 19.01.17 | 10:15 | 03.11.018 | Tinsley Oden (ICES) | OPAL: the Occam Plausibility Algorithm for Bayesian Model Selection and Validation | ||
| 02.02.17 | 10:15 | 03.11.018 | Steven Mattis (M2) | Stuart(2010) - Inverse Problems: A Bayesian Perspective (§1-3) | ||
| 22.02.17 | 14:15 | - | Jonas Latz (M2) | Stuart(2010) - Inverse Problems: A Bayesian Perspective (§4-5) |