Zhaozhi Qian | DeepAI

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Featured Co-authors

Mihaela van der Schaar
138 publications
Hao Sun
91 publications
Ahmed M. Alaa
24 publications
Franz J Király
24 publications
Yangming Li
21 publications
Jeroen Berrevoets
15 publications
Ioana Bica
15 publications
Alexis Bellot
13 publications
Nabeel Seedat
13 publications
Jonathan Crabbé
12 publications
Fergus Imrie
9 publications

∙ 08/09/2023

Do Diffusion Models Suffer Error Propagation? Theoretical Analysis and Consistency Regularization

While diffusion models have achieved promising performances in data synt...

0 Yangming Li, et al. ∙

∙ 05/31/2023

Learning Representations without Compositional Assumptions

This paper addresses unsupervised representation learning on tabular dat...

7 Tennison Liu, et al. ∙

∙ 05/16/2023

Synthetic data, real errors: how (not) to publish and use synthetic data

Generating synthetic data through generative models is gaining interest ...

1 Boris van Breugel, et al. ∙

∙ 03/03/2023

Causal Deep Learning

Causality has the potential to truly transform the way we solve a large ...

0 Jeroen Berrevoets, et al. ∙

∙ 02/24/2023

Neural Laplace Control for Continuous-time Delayed Systems

Many real-world offline reinforcement learning (RL) problems involve con...

0 Samuel Holt, et al. ∙

∙ 02/24/2023

Membership Inference Attacks against Synthetic Data through Overfitting Detection

Data is the foundation of most science. Unfortunately, sharing data can ...

3 Boris van Breugel, et al. ∙

∙ 01/18/2023

Synthcity: facilitating innovative use cases of synthetic data in different data modalities

Synthcity is an open-source software package for innovative use cases of...

9 Zhaozhi Qian, et al. ∙

∙ 12/01/2022

Navigating causal deep learning

Causal deep learning (CDL) is a new and important research area in the l...

7 Jeroen Berrevoets, et al. ∙

∙ 06/21/2022

D-CIPHER: Discovery of Closed-form PDEs

Closed-form differential equations, including partial differential equat...

0 Krzysztof Kacprzyk, et al. ∙

∙ 06/16/2022

Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations

Estimating counterfactual outcomes over time has the potential to unlock...

4 Nabeel Seedat, et al. ∙

∙ 06/10/2022

Neural Laplace: Learning diverse classes of differential equations in the Laplace domain

Neural Ordinary Differential Equations model dynamical systems with ODEs...

2 Samuel Holt, et al. ∙

∙ 10/28/2021

Explaining Latent Representations with a Corpus of Examples

Modern machine learning models are complicated. Most of them rely on con...

13 Jonathan Crabbé, et al. ∙

∙ 06/05/2021

Integrating Expert ODEs into Neural ODEs: Pharmacology and Disease Progression

Modeling a system's temporal behaviour in reaction to external stimuli i...

13 Zhaozhi Qian, et al. ∙

∙ 02/11/2021

Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge

Selecting causal inference models for estimating individualized treatmen...

4 Trent Kyono, et al. ∙

∙ 07/27/2020

CPAS: the UK's National Machine Learning-based Hospital Capacity Planning System for COVID-19

The coronavirus disease 2019 (COVID-19) global pandemic poses the threat...

23 Zhaozhi Qian, et al. ∙

∙ 06/26/2020

Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift

Modern neural networks have proven to be powerful function approximators...

5 Alex J. Chan, et al. ∙

∙ 05/13/2020

When and How to Lift the Lockdown? Global COVID-19 Scenario Analysis and Policy Assessment using Compartmental Gaussian Processes

The coronavirus disease 2019 (COVID-19) global pandemic has led many cou...

0 Zhaozhi Qian, et al. ∙

∙ 05/13/2020

When to Lift the Lockdown? Global COVID-19 Scenario Planning and Policy Effects using Compartmental Gaussian Processes

The coronavirus disease 2019 (COVID-19) outbreak has led government offi...

0 Zhaozhi Qian, et al. ∙

∙ 01/08/2020

Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes

Comorbid diseases co-occur and progress via complex temporal patterns th...

0 Zhaozhi Qian, et al. ∙

∙ 01/27/2017

Modelling Competitive Sports: Bradley-Terry-Élő Models for Supervised and On-Line Learning of Paired Competition Outcomes

Prediction and modelling of competitive sports outcomes has received muc...

0 Franz J Király, et al. ∙

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