322 citations · 915 across the 42 of their papers we have counts for
6 papers · 1 filter
Symmetry-Informed Causal Partial Identification
Uzair Akbar, Zulfiqar Zaidi, Niki Kilbertus +2
Partial identification (PI) entails estimating bounds on causal effects by encoding different assumptions on data generation as a constrained optimization problem. Such bounds can…
OrthoReg: Orthogonal Regularization for Hybrid Symbolic-Neural Dynamical Systems
Till Richter, Niki Kilbertus
Dynamical systems are fundamental to modeling the natural world, yet modeling them involves a persistent trade-off: manually prescribed mechanistic models are interpretable by desi…
Decomposing Ensemble Spread in Lorenz '96 With Learned Stochastic Parameterizations
Birgit Kühbacher, Daan Crommelin, Niki Kilbertus
Weather and climate forecasts are inherently uncertain due to chaotic dynamics, imperfect initial conditions, and incomplete representation of the underlying physical processes. Op…
Limits of Learning Linear Dynamics from Experiments
Aybüke Ulusarslan, Niki Kilbertus, Nora Schneider
Learning governing dynamics from data is a common goal across the sciences, yet it is only well-posed when the underlying mechanisms are identifiable. In practice, many data-driven…
Debiased neural operators for estimating functionals
Konstantin Hess, Dennis Frauen, Niki Kilbertus +1
Neural operators are widely used to approximate solution maps of complex physical systems. In many applications, however, the goal is not to recover the full solution trajectory, b…
Conservative Continuous-Time Treatment Optimization
Nora Schneider, Georg Manten, Niki Kilbertus
We develop a conservative continuous-time stochastic control framework for treatment optimization from irregularly sampled patient trajectories. The unknown patient dynamics are mo…