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Zhaozhi Qian
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2020 – today
- 2024
- [c25]Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar:
Adaptive Experiment Design with Synthetic Controls. AISTATS 2024: 1180-1188 - [c24]Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar:
DAGnosis: Localized Identification of Data Inconsistencies using Structures. AISTATS 2024: 1864-1872 - [c23]Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar:
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference. ICLR 2024 - [i25]Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar:
Deep Generative Symbolic Regression. CoRR abs/2401.00282 (2024) - [i24]Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar:
Adaptive Experiment Design with Synthetic Controls. CoRR abs/2401.17205 (2024) - [i23]Nicolas Huynh, Jeroen Berrevoets, Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar:
DAGnosis: Localized Identification of Data Inconsistencies using Structures. CoRR abs/2402.17599 (2024) - [i22]Krzysztof Kacprzyk, Samuel Holt, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar:
ODE Discovery for Longitudinal Heterogeneous Treatment Effects Inference. CoRR abs/2403.10766 (2024) - 2023
- [j3]Trent Kyono
, Ioana Bica
, Zhaozhi Qian
, Mihaela van der Schaar
:
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. ACM Trans. Comput. Heal. 4(2): 15:1-15:29 (2023) - [c22]Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar:
Neural Laplace Control for Continuous-time Delayed Systems. AISTATS 2023: 1747-1778 - [c21]Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar:
Membership Inference Attacks against Synthetic Data through Overfitting Detection. AISTATS 2023: 3493-3514 - [c20]Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar:
Deep Generative Symbolic Regression. ICLR 2023 - [c19]Alihan Hüyük, Zhaozhi Qian, Mihaela van der Schaar:
When to Make and Break Commitments? ICLR 2023 - [c18]Tennison Liu, Zhaozhi Qian, Jeroen Berrevoets, Mihaela van der Schaar:
GOGGLE: Generative Modelling for Tabular Data by Learning Relational Structure. ICLR 2023 - [c17]Tennison Liu, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar:
Learning Representations without Compositional Assumptions. ICML 2023: 21388-21403 - [c16]Boris van Breugel, Zhaozhi Qian, Mihaela van der Schaar:
Synthetic Data, Real Errors: How (Not) to Publish and Use Synthetic Data. ICML 2023: 34793-34808 - [c15]Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar:
D-CIPHER: Discovery of Closed-form Partial Differential Equations. NeurIPS 2023 - [c14]Zhaozhi Qian, Robert Davis, Mihaela van der Schaar:
Synthcity: a benchmark framework for diverse use cases of tabular synthetic data. NeurIPS 2023 - [c13]Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar:
TRIAGE: Characterizing and auditing training data for improved regression. NeurIPS 2023 - [i21]Zhaozhi Qian, Bogdan-Constantin Cebere, Mihaela van der Schaar:
Synthcity: facilitating innovative use cases of synthetic data in different data modalities. CoRR abs/2301.07573 (2023) - [i20]Boris van Breugel, Hao Sun, Zhaozhi Qian, Mihaela van der Schaar:
Membership Inference Attacks against Synthetic Data through Overfitting Detection. CoRR abs/2302.12580 (2023) - [i19]Samuel Holt, Alihan Hüyük, Zhaozhi Qian, Hao Sun, Mihaela van der Schaar:
Neural Laplace Control for Continuous-time Delayed Systems. CoRR abs/2302.12604 (2023) - [i18]Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar:
Causal Deep Learning. CoRR abs/2303.02186 (2023) - [i17]Boris van Breugel, Zhaozhi Qian, Mihaela van der Schaar:
Synthetic data, real errors: how (not) to publish and use synthetic data. CoRR abs/2305.09235 (2023) - [i16]Tennison Liu, Jeroen Berrevoets, Zhaozhi Qian, Mihaela van der Schaar:
Learning Representations without Compositional Assumptions. CoRR abs/2305.19726 (2023) - [i15]Yangming Li, Zhaozhi Qian, Mihaela van der Schaar:
Do Diffusion Models Suffer Error Propagation? Theoretical Analysis and Consistency Regularization. CoRR abs/2308.05021 (2023) - [i14]Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole
, Mihaela van der Schaar:
Clairvoyance: A Pipeline Toolkit for Medical Time Series. CoRR abs/2310.18688 (2023) - [i13]Nabeel Seedat, Jonathan Crabbé, Zhaozhi Qian, Mihaela van der Schaar:
TRIAGE: Characterizing and auditing training data for improved regression. CoRR abs/2310.18970 (2023) - 2022
- [j2]Cong Shen, Zhaozhi Qian, Alihan Hüyük, Mihaela van der Schaar:
MARS: Assisting Human with Information Processing Tasks Using Machine Learning. ACM Trans. Comput. Heal. 3(2): 21:1-21:19 (2022) - [c12]Zhaozhi Qian, Krzysztof Kacprzyk, Mihaela van der Schaar:
D-CODE: Discovering Closed-form ODEs from Observed Trajectories. ICLR 2022 - [c11]Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar:
Neural Laplace: Learning diverse classes of differential equations in the Laplace domain. ICML 2022: 8811-8832 - [c10]Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar:
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. ICML 2022: 19497-19521 - [i12]Samuel Holt, Zhaozhi Qian, Mihaela van der Schaar:
Neural Laplace: Learning diverse classes of differential equations in the Laplace domain. CoRR abs/2206.04843 (2022) - [i11]Nabeel Seedat, Fergus Imrie, Alexis Bellot, Zhaozhi Qian, Mihaela van der Schaar:
Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations. CoRR abs/2206.08311 (2022) - [i10]Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar:
D-CIPHER: Discovery of Closed-form PDEs. CoRR abs/2206.10586 (2022) - [i9]Jeroen Berrevoets, Krzysztof Kacprzyk, Zhaozhi Qian, Mihaela van der Schaar:
Navigating causal deep learning. CoRR abs/2212.00911 (2022) - 2021
- [j1]Zhaozhi Qian
, Ahmed M. Alaa, Mihaela van der Schaar:
CPAS: the UK's national machine learning-based hospital capacity planning system for COVID-19. Mach. Learn. 110(1): 15-35 (2021) - [c9]Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar:
Clairvoyance: A Pipeline Toolkit for Medical Time Series. ICLR 2021 - [c8]Jeroen Berrevoets, Ahmed M. Alaa, Zhaozhi Qian, James Jordon, Alexander E. S. Gimson, Mihaela van der Schaar:
Learning Queueing Policies for Organ Transplantation Allocation using Interpretable Counterfactual Survival Analysis. ICML 2021: 792-802 - [c7]Zhaozhi Qian, Yao Zhang, Ioana Bica, Angela M. Wood, Mihaela van der Schaar:
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes. NeurIPS 2021: 3178-3190 - [c6]Zhaozhi Qian, William R. Zame, Lucas M. Fleuren, Paul W. G. Elbers, Mihaela van der Schaar:
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression. NeurIPS 2021: 11364-11383 - [c5]Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar:
Explaining Latent Representations with a Corpus of Examples. NeurIPS 2021: 12154-12166 - [c4]Zhaozhi Qian, Alicia Curth, Mihaela van der Schaar:
Estimating Multi-cause Treatment Effects via Single-cause Perturbation. NeurIPS 2021: 23754-23767 - [i8]Trent Kyono, Ioana Bica, Zhaozhi Qian, Mihaela van der Schaar:
Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. CoRR abs/2102.06271 (2021) - [i7]Zhaozhi Qian, William R. Zame, Lucas M. Fleuren, Paul W. G. Elbers, Mihaela van der Schaar:
Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression. CoRR abs/2106.02875 (2021) - [i6]Jonathan Crabbé, Zhaozhi Qian, Fergus Imrie, Mihaela van der Schaar:
Explaining Latent Representations with a Corpus of Examples. CoRR abs/2110.15355 (2021) - 2020
- [c3]Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Mihaela van der Schaar, Jem Rashbass:
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. AISTATS 2020: 3295-3305 - [c2]Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar:
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift. ICML 2020: 1392-1402 - [c1]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes. NeurIPS 2020 - [i5]Zhaozhi Qian, Ahmed M. Alaa, Alexis Bellot, Jem Rashbass, Mihaela van der Schaar:
Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes. CoRR abs/2001.02585 (2020) - [i4]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
When to Lift the Lockdown? Global COVID-19 Scenario Planning and Policy Effects using Compartmental Gaussian Processes. CoRR abs/2005.08837 (2020) - [i3]Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar:
Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift. CoRR abs/2006.14988 (2020) - [i2]Zhaozhi Qian, Ahmed M. Alaa, Mihaela van der Schaar:
CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19. CoRR abs/2007.13825 (2020)
2010 – 2019
- 2017
- [i1]Franz J. Király, Zhaozhi Qian:
Modelling Competitive Sports: Bradley-Terry-Élő Models for Supervised and On-Line Learning of Paired Competition Outcomes. CoRR abs/1701.08055 (2017)
Coauthor Index
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