← Authors

Niki Kilbertus

24 papers · 2017–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge 🧭 Keyword Pioneer 🌍 Conference Polyglot (7) πŸƒ Academic Marathon (8) 🐝 Cross-Pollinator (6) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (31) πŸ† Grand Slam 🌱 Topic Pioneer πŸ‘‘ Triple Crown πŸš€ Conference Pioneer πŸ’Ž Century Club (24) πŸ”₯ Unstoppable (9) πŸ—ƒοΈ Keyword Collector (79) πŸ“ˆ Trend Setter ⚑ Prolific Year (5)

Conferences

ICML (7) NIPS (7) ICLR (4) CLEAR (3) AAAI (1) AISTATS (1) UAI (1)

Top co-authors

Bernhard SchΓΆlkopf (5) Ricardo Silva (3) Cecilia Casolo (3) Giambattista Parascandolo (3) Jason Hartford (2) SΓΈren Wengel Mogensen (2) Adrian Weller (2) Jiri Hron (2) Georg Manten (2) SΓΆren Becker (2)

Keywords

causal inference (5) dynamical system (2) causal effect (2) transfer learning (2) partial identification (2) instrumental variable (2) decision policy (1) domain generalization (1) generative modeling (1) constrained optimization (1) utility optimization (1) kernel estimation (1) out-of-distribution generalization (1) secure multi-party computation (1) algorithmic fairness (1) sensitivity analysis (1) experimental design (1) gradient-based optimization (1) machine learning (1) learning to rank (1)

Papers

Your Assumed DAG is Wrong And Here’s How To Deal With It CLEAR 2025
Whole Genome Transformer for Gene Interaction Effects in Microbiome Habitat Specificity AAAI 2025
Learning Representations of Instruments for Partial Identification of Treatment Effects ICML 2025
Signature Kernel Conditional Independence Tests in Causal Discovery for Stochastic Processes ICLR 2025
An Asymmetric Independence Model for Causal Discovery on Path Spaces CLEAR 2025
Generative Intervention Models for Causal Perturbation Modeling ICML 2025
Unbalancedness in Neural Monge Maps Improves Unpaired Domain Translation ICLR 2024
ODEFormer: Symbolic Regression of Dynamical Systems with Transformers ICLR 2024
Targeted Sequential Indirect Experiment Design NIPS 2024
Sequential Underspecified Instrument Selection for Cause-Effect Estimation ICML 2023
Stabilized Neural Differential Equations for Learning Dynamics with Explicit Constraints NIPS 2023
Stochastic Causal Programming for Bounding Treatment Effects CLEAR 2023
Modeling content creator incentives on algorithm-curated platforms ICLR 2023
Predicting Ordinary Differential Equations with Transformers ICML 2023
Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution NIPS 2022
Sparsity in Continuous-Depth Neural Networks NIPS 2022
On Component Interactions in Two-Stage Recommender Systems NIPS 2021
On Disentangled Representations Learned from Correlated Data ICML 2021
A Class of Algorithms for General Instrumental Variable Models NIPS 2020
Fair Decisions Despite Imperfect Predictions AISTATS 2020
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding UAI 2019
Learning Independent Causal Mechanisms ICML 2018
Blind Justice: Fairness with Encrypted Sensitive Attributes ICML 2018
Avoiding Discrimination through Causal Reasoning NIPS 2017