Niki Kilbertus

CoRR, October, 2025

Predicting symbolic ODEs from multiple trajectories.

[BibT_eX]

[DOI]

Yakup Emre Sahin

CoRR, October, 2025

Identifiability Challenges in Sparse Linear Ordinary Differential Equations.

[BibT_eX]

[DOI]

CoRR, June, 2025

Learning Representations of Instruments for Partial Identification of Treatment Effects.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Generative Intervention Models for Causal Perturbation Modeling.

[BibT_eX]

[DOI]

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes.

[BibT_eX]

[DOI]

Georg Manten

Emilio Ferrucci

Søren Wengel Mogensen

Cristopher Salvi

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Your Assumed DAG is Wrong And Here's How To Deal With It.

[BibT_eX]

[DOI]

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

An Asymmetric Independence Model for Causal Discovery on Path Spaces.

[BibT_eX]

[DOI]

Georg Manten

Søren Wengel Mogensen

Sandeep Suresh Cranganore

Proceedings of the Causal Learning and Reasoning, Lausanne, Switzerland, 7-9 May 2025., 2025

Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity.

[BibT_eX]

[DOI]

Zhufeng Li

Nicholas D. Youngblut

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Learning Counterfactually Invariant Predictors.

[BibT_eX]

[DOI]

Trans. Mach. Learn. Res., 2024

Projected Neural Differential Equations for Learning Constrained Dynamics.

[BibT_eX]

[DOI]

CoRR, 2024

Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series.

[BibT_eX]

[DOI]

Thomas Schwarz

CoRR, 2024

Causal machine learning for predicting treatment outcomes.

[BibT_eX]

[DOI]

Mihaela van der Schaar

CoRR, 2024

Targeted Sequential Indirect Experiment Design.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Towards Physically Consistent Deep Learning For Climate Model Parameterizations.

[BibT_eX]

[DOI]

Birgit Kühbacher

Fernando Iglesias-Suarez

Veronika Eyring

Proceedings of the International Conference on Machine Learning and Applications, 2024

ODEFormer: Symbolic Regression of Dynamical Systems with Transformers.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation.

[BibT_eX]

[DOI]

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Supervised learning and model analysis with compositional data.

[BibT_eX]

[DOI]

PLoS Comput. Biol., 2023

Stabilized Neural Differential Equations for Learning Constrained Dynamics.

[BibT_eX]

[DOI]

CoRR, 2023

Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Predicting Ordinary Differential Equations with Transformers.

[BibT_eX]

[DOI]

Michal Klein

Alexander Neitz

Proceedings of the International Conference on Machine Learning, 2023

Sequential Underspecified Instrument Selection for Cause-Effect Estimation.

[BibT_eX]

[DOI]

Elisabeth Ailer

Jason S. Hartford

Proceedings of the International Conference on Machine Learning, 2023

Modeling content creator incentives on algorithm-curated platforms.

[BibT_eX]

[DOI]

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Stochastic Causal Programming for Bounding Treatment Effects.

[BibT_eX]

[DOI]

Proceedings of the Conference on Causal Learning and Reasoning, 2023

2022

Discovering ordinary differential equations that govern time-series.

[BibT_eX]

[DOI]

Michal Klein

Alexander Neitz

CoRR, 2022

Predicting single-cell perturbation responses for unseen drugs.

[BibT_eX]

[DOI]

CoRR, 2022

Numerical Analysis of the Causal Action Principle in Low Dimensions.

[BibT_eX]

[DOI]

Felix Finster

Robert H. Jonsson

CoRR, 2022

Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Sparsity in Continuous-Depth Neural Networks.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Multi-disciplinary fairness considerations in machine learning for clinical trials.

[BibT_eX]

[DOI]

Proceedings of the FAccT '22: 2022 ACM Conference on Fairness, Accountability, and Transparency, Seoul, Republic of Korea, June 21, 2022

2021

Beyond Predictions in Neural ODEs: Identification and Interventions.

[BibT_eX]

[DOI]

Hananeh Aliee

Fabian J. Theis

CoRR, 2021

A causal view on compositional data.

[BibT_eX]

[DOI]

Elisabeth Ailer

Christian L. Müller

CoRR, 2021

Beyond traditional assumptions in fair machine learning.

[BibT_eX]

[DOI]

CoRR, 2021

On Component Interactions in Two-Stage Recommender Systems.

[BibT_eX]

[DOI]

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

On Disentangled Representations Learned from Correlated Data.

[BibT_eX]

[DOI]

Proceedings of the 38th International Conference on Machine Learning, 2021

2020

Beyond traditional assumptions in fair machine learning

[BibT_eX]

[DOI]

PhD thesis, 2020

Exploration in two-stage recommender systems.

[BibT_eX]

[DOI]

CoRR, 2020

Is Independence all you need? On the Generalization of Representations Learned from Correlated Data.

[BibT_eX]

[DOI]

CoRR, 2020

A Class of Algorithms for General Instrumental Variable Models.

[BibT_eX]

[DOI]

Matt J. Kusner

Ricardo Silva

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Fair Decisions Despite Imperfect Predictions.

[BibT_eX]

[DOI]

Manuel Gomez Rodriguez

Krikamol Muandet

Isabel Valera

Proceedings of the 23rd International Conference on Artificial Intelligence and Statistics, 2020

2019

Convolutional neural networks: a magic bullet for gravitational-wave detection?

[BibT_eX]

[DOI]

CoRR, 2019

Improving Consequential Decision Making under Imperfect Predictions.

[BibT_eX]

[DOI]

Manuel Gomez-Rodriguez

Krikamol Muandet

Isabel Valera

CoRR, 2019

The Sensitivity of Counterfactual Fairness to Unmeasured Confounding.

[BibT_eX]

[DOI]

Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

2018

Generalization in anti-causal learning.

[BibT_eX]

[DOI]

CoRR, 2018

Learning Independent Causal Mechanisms.

[BibT_eX]

[DOI]

Mateo Rojas-Carulla

Proceedings of the 35th International Conference on Machine Learning, 2018

Blind Justice: Fairness with Encrypted Sensitive Attributes.

[BibT_eX]

[DOI]

Proceedings of the 35th International Conference on Machine Learning, 2018

2017

Avoiding Discrimination through Causal Reasoning.

[BibT_eX]

[DOI]

Mateo Rojas-Carulla

Moritz Hardt

Dominik Janzing