Kilbertus, Niki

34 publications

NeurIPS 2025 An Analysis of Causal Effect Estimation Using Outcome Invariant Data Augmentation Uzair Akbar, Niki Kilbertus, Hao Shen, Krikamol Muandet, Bo Dai

CLeaR 2025 An Asymmetric Independence Model for Causal Discovery on Path Spaces Georg Manten, Cecilia Casolo, Søren Wengel Mogensen, Niki Kilbertus

ICML 2025 Generative Intervention Models for Causal Perturbation Modeling Nora Schneider, Lars Lorch, Niki Kilbertus, Bernhard Schölkopf, Andreas Krause

ICML 2025 Learning Representations of Instruments for Partial Identification of Treatment Effects Jonas Schweisthal, Dennis Frauen, Maresa Schröder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel

ICLRW 2025 Learning Representations of Instruments for Partial Identification of Treatment Effects Jonas Schweisthal, Dennis Frauen, Maresa Schröder, Konstantin Hess, Niki Kilbertus, Stefan Feuerriegel

ICLR 2025 Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes Georg Manten, Cecilia Casolo, Emilio Ferrucci, Søren Wengel Mogensen, Cristopher Salvi, Niki Kilbertus

AAAI 2025 Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity Zhufeng Li, Sandeep Suresh Cranganore, Nicholas D. Youngblut, Niki Kilbertus

CLeaR 2025 Your Assumed DAG Is Wrong and Here’s How to Deal with It Kirtan Padh, Zhufeng Li, Cecilia Casolo, Niki Kilbertus

TMLR 2024 Learning Counterfactually Invariant Predictors Francesco Quinzan, Cecilia Casolo, Krikamol Muandet, Yucen Luo, Niki Kilbertus

ICLR 2024 ODEFormer: Symbolic Regression of Dynamical Systems with Transformers Stéphane d'Ascoli, Sören Becker, Philippe Schwaller, Alexander Mathis, Niki Kilbertus

NeurIPSW 2024 Projected Neural Differential Equations for Power Grid Modeling with Constraints Alistair White, Anna Büttner, Maximilian Gelbrecht, Niki Kilbertus, Frank Hellmann, Niklas Boers

NeurIPS 2024 Targeted Sequential Indirect Experiment Design Elisabeth Ailer, Niclas Dern, Jason Hartford, Niki Kilbertus

ICLR 2024 Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation Luca Eyring, Dominik Klein, Théo Uscidda, Giovanni Palla, Niki Kilbertus, Zeynep Akata, Fabian J Theis

NeurIPSW 2024 Uncertainty-Aware Optimal Treatment Selection for Clinical Time Series Thomas Schwarz, Cecilia Casolo, Niki Kilbertus

ICLRW 2024 Whole Genome Transformers for Gene Interaction Effects in Microbiome Habitat Prediction Zhufeng Li, Sandeep Suresh Cranganore, Nicholas Youngblut, Niki Kilbertus

ICLR 2023 Modeling Content Creator Incentives on Algorithm-Curated Platforms Jiri Hron, Karl Krauth, Michael Jordan, Niki Kilbertus, Sarah Dean

ICML 2023 Predicting Ordinary Differential Equations with Transformers Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo, Niki Kilbertus

ICML 2023 Sequential Underspecified Instrument Selection for Cause-Effect Estimation Elisabeth Ailer, Jason Hartford, Niki Kilbertus

NeurIPS 2023 Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints Alistair White, Niki Kilbertus, Maximilian Gelbrecht, Niklas Boers

CLeaR 2023 Stochastic Causal Programming for Bounding Treatment Effects Kirtan Padh, Jakob Zeitler, David Watson, Matt Kusner, Ricardo Silva, Niki Kilbertus

NeurIPSW 2022 Discovering Ordinary Differential Equations That Govern Time-Series Sören Becker, Michal Klein, Alexander Neitz, Giambattista Parascandolo, Niki Kilbertus

NeurIPSW 2022 Modeling Single-Cell Dynamics Using Unbalanced Parameterized Monge Maps Luca Eyring, Dominik Klein, Giovanni Palla, Sören Becker, Philipp Weiler, Niki Kilbertus, Fabian J Theis

NeurIPSW 2022 Partial Identification Without Distributional Assumptions Kirtan Padh, Jakob Zeitler, David Watson, Matt Kusner, Ricardo Silva, Niki Kilbertus

NeurIPS 2022 Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution Leon Hetzel, Simon Boehm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian J. Theis

ICLRW 2022 Predicting Single-Cell Perturbation Responses for Unseen Drugs Leon Hetzel, Simon Boehm, Niki Kilbertus, Stephan Günnemann, Mohammad Lotfollahi, Fabian J Theis

NeurIPS 2022 Sparsity in Continuous-Depth Neural Networks Hananeh Aliee, Till Richter, Mikhail Solonin, Ignacio Ibarra, Fabian J. Theis, Niki Kilbertus

NeurIPS 2021 On Component Interactions in Two-Stage Recommender Systems Jiri Hron, Karl Krauth, Michael I. Jordan, Niki Kilbertus

ICML 2021 On Disentangled Representations Learned from Correlated Data Frederik Träuble, Elliot Creager, Niki Kilbertus, Francesco Locatello, Andrea Dittadi, Anirudh Goyal, Bernhard Schölkopf, Stefan Bauer

NeurIPS 2020 A Class of Algorithms for General Instrumental Variable Models Niki Kilbertus, Matt J Kusner, Ricardo Silva

AISTATS 2020 Fair Decisions Despite Imperfect Predictions Niki Kilbertus, Manuel Gomez Rodriguez, Bernhard Schölkopf, Krikamol Muandet, Isabel Valera

UAI 2019 The Sensitivity of Counterfactual Fairness to Unmeasured Confounding Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva

ICML 2018 Blind Justice: Fairness with Encrypted Sensitive Attributes Niki Kilbertus, Adria Gascon, Matt Kusner, Michael Veale, Krishna Gummadi, Adrian Weller

ICML 2018 Learning Independent Causal Mechanisms Giambattista Parascandolo, Niki Kilbertus, Mateo Rojas-Carulla, Bernhard Schölkopf

NeurIPS 2017 Avoiding Discrimination Through Causal Reasoning Niki Kilbertus, Mateo Rojas Carulla, Giambattista Parascandolo, Moritz Hardt, Dominik Janzing, Bernhard Schölkopf