322 citations · 915 across the 42 of their papers we have counts for
7 papers · 1 filter
Discovering ordinary differential equations that govern time-series
Sören Becker, Michal Klein, Alexander Neitz +2
Natural laws are often described through differential equations yet finding a differential equation that describes the governing law underlying observed data is a challenging and s…
Sparsity in Continuous-Depth Neural Networks
Hananeh Aliee, Till Richter, Mikhail Solonin +3
Neural Ordinary Differential Equations (NODEs) have proven successful in learning dynamical systems in terms of accurately recovering the observed trajectories. While different typ…
Learning Counterfactually Invariant Predictors
Francesco Quinzan, Cecilia Casolo, Krikamol Muandet +2
Notions of counterfactual invariance (CI) have proven essential for predictors that are fair, robust, and generalizable in the real world. We propose graphical criteria that yield…
Modeling Content Creator Incentives on Algorithm-Curated Platforms
Jiri Hron, Karl Krauth, Michael I. Jordan +2
Content creators compete for user attention. Their reach crucially depends on algorithmic choices made by developers on online platforms. To maximize exposure, many creators adapt…
Supervised Learning and Model Analysis with Compositional Data
Shimeng Huang, Elisabeth Ailer, Niki Kilbertus +1
The compositionality and sparsity of high-throughput sequencing data poses a challenge for regression and classification. However, in microbiome research in particular, conditional…
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution
Leon Hetzel, Simon Böhm, Niki Kilbertus +3
Single-cell transcriptomics enabled the study of cellular heterogeneity in response to perturbations at the resolution of individual cells. However, scaling high-throughput screens…
Numerical Analysis of the Causal Action Principle in Low Dimensions
Felix Finster, Robert H. Jonsson, Niki Kilbertus
The numerical analysis of causal fermion systems is advanced by employing differentiable programming methods. The causal action principle for weighted counting measures is introduc…