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Discovering ordinary differential equations that govern time-series


Nov 05, 2022
Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo, Niki Kilbertus

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* Workshop paper at NeurIPS 2022 workshop "AI for Science" 

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Sparsity in Continuous-Depth Neural Networks


Oct 26, 2022
Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian Theis, Niki Kilbertus

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* Neurips 2022 

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Learning Counterfactually Invariant Predictors


Jul 20, 2022
Francesco Quinzan, Cecilia Casolo, Krikamol Muandet, Niki Kilbertus, Yucen Luo

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Modeling Content Creator Incentives on Algorithm-Curated Platforms


Jun 27, 2022
Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus, Sarah Dean

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Multi-disciplinary fairness considerations in machine learning for clinical trials


May 18, 2022
Isabel Chien, Nina Deliu, Richard E. Turner, Adrian Weller, Sofia S. Villar, Niki Kilbertus

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* Appeared at ACM FAccT 2022 

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Supervised Learning and Model Analysis with Compositional Data


May 15, 2022
Shimeng Huang, Elisabeth Ailer, Niki Kilbertus, Niklas Pfister

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Predicting single-cell perturbation responses for unseen drugs


Apr 28, 2022
Leon Hetzel, Simon Böhm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian Theis

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* ICLR 2022 workshop paper at Workshop "Machine Learning for Drug Discovery" 
* 8 pages 

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Stochastic Causal Programming for Bounding Treatment Effects


Feb 22, 2022
Kirtan Padh, Jakob Zeitler, David Watson, Matt Kusner, Ricardo Silva, Niki Kilbertus

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On component interactions in two-stage recommender systems


Jun 28, 2021
Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus

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Beyond Predictions in Neural ODEs: Identification and Interventions


Jun 23, 2021
Hananeh Aliee, Fabian J. Theis, Niki Kilbertus

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