ติดตาม
Niki Kilbertus
Niki Kilbertus
Technical University of Munich & Helmholtz Munich
ยืนยันอีเมลแล้วที่ tum.de - หน้าแรก
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อ้างโดย
อ้างโดย
ปี
Avoiding discrimination through causal reasoning
N Kilbertus, M Rojas Carulla, G Parascandolo, M Hardt, D Janzing, ...
Advances in neural information processing systems, NeurIPS 30, 2017
7682017
Learning Independent Causal Mechanisms
G Parascandolo, N Kilbertus, M Rojas-Carulla, B Schölkopf
International Conference on Machine Learning, ICML 2018, 2018
1982018
Blind Justice: Fairness with Encrypted Sensitive Attributes
N Kilbertus, A Gascón, MJ Kusner, M Veale, KP Gummadi, A Weller
International Conference on Machine Learning, ICML 2018, 2018
1862018
Convolutional neural networks: A magic bullet for gravitational-wave detection?
N Kilbertus, TD Gebhard, I Harry, B Schölkopf
Physical Review D 100 (6), 063015, 2019
162*2019
On disentangled representations learned from correlated data
F Träuble, E Creager, N Kilbertus, A Goyal, F Locatello, B Schölkopf, ...
International Conference on Machine Learning, ICML 2021, 2021
1392021
Causal machine learning for predicting treatment outcomes
S Feuerriegel, D Frauen, V Melnychuk, J Schweisthal, K Hess, A Curth, ...
Nature Medicine 30 (4), 958-968, 2024
1102024
The sensitivity of counterfactual fairness to unmeasured confounding
N Kilbertus, PJ Ball, MJ Kusner, A Weller, R Silva
Conference on Uncertainty in Artificial Intelligence, UAI 2019, 2019
732019
Fair decisions despite imperfect predictions
N Kilbertus, M Gomez-Rodriguez, B Schölkopf, K Muandet, I Valera
Conference on Artificial Intelligence and Statistics, AISTATS 2019, 2019
692019
Predicting single-cell perturbation responses for unseen drugs
L Hetzel, S Böhm, N Kilbertus, S Günnemann, M Lotfollahi, F Theis
Neural Information Processing Systems (NeurIPS) 2022, 2022
68*2022
Generalization in anti-causal learning
N Kilbertus, G Parascandolo, B Schölkopf
NeurIPS 2018 Workshop on Critiquing and Correcting Trends in Machine Learning, 2018
632018
A Class of Algorithms for General Instrumental Variable Models
N Kilbertus, MJ Kusner, R Silva
Neural Information Processing Systems (NeurIPS) 2020, 2020
482020
Universal hydrodynamic flow in holographic planar shock collisions
PM Chesler, N Kilbertus, W van der Schee
Journal of High Energy Physics 2015 (11), 1-21, 2015
422015
Modeling content creator incentives on algorithm-curated platforms
J Hron, K Krauth, MI Jordan, N Kilbertus, S Dean
International Conference on Learning Representations (ICLR), 2023, 2022
412022
On component interactions in two-stage recommender systems
J Hron, K Krauth, MI Jordan, N Kilbertus
Neural Information Processing Systems (NeurIPS) 2021, 2021
392021
Multi-disciplinary fairness considerations in machine learning for clinical trials
I Chien, N Deliu, R Turner, A Weller, S Villar, N Kilbertus
Proceedings of the 2022 ACM Conference on Fairness, Accountability, and …, 2022
302022
Stochastic Causal Programming for Bounding Treatment Effects
K Padh, J Zeitler, D Watson, M Kusner, R Silva, N Kilbertus
Conference on Causal Learning and Reasoning (CLeaR), 2023, 2022
272022
Odeformer: Symbolic regression of dynamical systems with transformers
S d'Ascoli, S Becker, A Mathis, P Schwaller, N Kilbertus
International Conference on Learning Representations, ICLR, 2024
212024
Quod erat knobelandum
C Löh, S Krauss, N Kilbertus
Springer Berlin Heidelberg, 2016
202016
Predicting ordinary differential equations with transformers
S Becker, M Klein, A Neitz, G Parascandolo, N Kilbertus
International Conference on Machine Learning, ICML, 1978-2002, 2023
19*2023
CONVWAVE: Searching for Gravitational Waves with Fully Convolutional Neural Nets
T Gebhard, N Kilbertus, G Parascandolo, I Harry, B Schölkopf
Workshop Deep Learning for Physical Sciences at NIPS 2017, 2017
182017
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บทความ 1–20