Niki Kilbertus
24 papers · 2017–2025 · 7 conferences · across top CS/AI conferences
Achievements
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๐ Academic Marathon (8) ๐งญ Keyword Pioneer ๐ Conference Polyglot (7) ๐ Interdisciplinary Bridge ๐ Cross-Pollinator (6)
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Cross-Pollinator
(6)
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Renaissance Researcher
(7)
๐บ๏ธ
Taxonomy Completionist
(31)
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Grand Slam
๐ฑ
Topic Pioneer
๐
Triple Crown
๐
Conference Pioneer
๐
Century Club
(24)
๐ฅ
Unstoppable
(9)
๐๏ธ
Keyword Collector
(79)
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Trend Setter
โก
Prolific Year
(5)
Conferences
ICML (7)
NIPS (7)
ICLR (4)
CLEAR (3)
AAAI (1)
AISTATS (1)
UAI (1)
Top co-authors
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 Hereโs 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