NeurIPS, ICML & ICLR Publications

2024

Mean-field Chaos Diffusion Models

Sungwoo Park, Dongjun Kim, Ahmed Alaa
ICML 2024 (Oral) /  Paper 

Prediction-powered Generalization of Causal Inferences

Ilker Demirel, Ahmed Alaa, Anthony Philippakis, David Sontag
ICML 2024 /  Paper 

InstructCV: Instruction-Tuned Text-to-Image Diffusion Models as Vision Generalists

Yulu Gan, Sungwoo Park, Alexander Schubert, Anthony Philippakis, Ahmed Alaa
ICLR 2024 / Paper / Code / Hugging Face Demo / Tweetorial

2023

Conformal meta-learners for predictive inference of individual treatment effects

Ahmed Alaa, Zaid Ahmad, Mark van der Laan
NeurIPS 2023 (Oral) /  Paper  / Code / Tweetorial / Talk

Aligning synthetic medical images with clinical knowledge using human feedback

Shenghuan Sun, Gregory M. Goldgof, Atul J. Butte, Ahmed Alaa
NeurIPS 2023 (Spotlight) / Paper / Code / Tweetorial

Diffinfinite: Large mask-image synthesis via parallel random patch diffusion in histopathology

Marco Aversa, Gabriel Nobis, Miriam Hägele, Kai Standvoss, Mihaela Chirica, Roderick Murray-Smith, Ahmed Alaa, Lukas Ruff, Daniela Ivanova, Wojciech Samek, Frederick Klauschen, Bruno Sanguinetti, Luis Oala
NeurIPS 2023 (Spotlight) /  Paper / Code / Project Website

2022

ETAB: A Benchmark Suite for Visual Representation Learning in Echocardiography

Ahmed Alaa, Anthony Philippakis, David Sontag
NeurIPS 2022 / Paper / Code

How faithful is your synthetic data? sample-level metrics for evaluating and auditing generative models

Ahmed Alaa, Boris van Breugel, Evgeny Saveliev, Mihaela van der Schaar
ICML 2022 / Paper / Code 

2021

Generative Time-series Modeling with Fourier Flows

Ahmed Alaa, Alex J. Chan, Mihaela van der Schaar
ICLR 2021 / Paper / Code

Conformal Time-series Forecasting

Kamile Stankeviciute, Ahmed Alaa, Mihaela van der Schaar 
NeurIPS 2021 / Paper / Code

Learning queueing policies for organ transplantation allocation using interpretable counterfactual survival analysis

Jeroen Berrevoets, Ahmed Alaa, Zhaozhi Qian, James Jordon, Alexander ES Gimson, Mihaela Van Der Schaar 
ICML 2021 / Paper / Code

2020

Discriminative Jackknife: Quantifying Uncertainty in Deep Learning via Higher-Order Influence Functions

Ahmed Alaa, Mihaela van der Schaar
ICML 2020 / Paper / Code

Frequentist Uncertainty in Recurrent Neural Networks via Blockwise Influence Functions

Ahmed Alaa, Mihaela van der Schaar
ICML 2020 / Paper / Code

Unlabelled Data Improves Bayesian Uncertainty Calibration under Covariate Shift

Alex J Chan, Ahmed Alaa, Zhaozhi Qian, Mihaela van der Schaar
ICML 2020 / Paper / Code

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

Zhaozhi Qian*, Ahmed Alaa*, Mihaela van der Schaar
NeurIPS 2020 / Paper

Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations

Ioana Bica, Ahmed Alaa, James Jordon, Mihaela van der Schaar
ICLR 2020 / Paper / Code

Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders

Ioana Bica, Ahmed Alaa, Mihaela van der Schaar
ICML 2020 / Paper / Code

2019

Validating Causal Inference Models via Influence Functions

Ahmed Alaa, Mihaela van der Schaar
ICML 2019 / Paper

Attentive state-space modeling of disease progression

Ahmed Alaa, Mihaela van der Schaar
NeurIPS 2019 / Paper / Code

Demystifying Black-box Models with Symbolic Metamodels

Ahmed Alaa, Mihaela van der Schaar
NeurIPS 2019 / Paper / Code

2018

Forecasting Treatment Responses Over Time Using Recurrent Marginal Structural Networks

Bryan Lim, Ahmed Alaa, Mihaela van der Schaar
NeurIPS 2018/ Paper / Code

AutoPrognosis: Automated Clinical Prognostic Modeling via Bayesian Optimization with Structured Kernel Learning

Ahmed Alaa, Mihaela van der Schaar
ICML 2018/ Paper / Code

Limits of estimating heterogeneous treatment effects: Guidelines for practical algorithm design

Ahmed Alaa, Mihaela van der Schaar
ICML 2018 / Paper 

2017

Deep multi-task gaussian processes for survival analysis with competing risks

Ahmed Alaa, Mihaela van der Schaar
NeurIPS 2017 (Spotlight) / Paper / Code 

Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes

Ahmed Alaa, Mihaela van der Schaar
NeurIPS 2017 / Paper / Code 

Learning from Clinical Judgments: Semi-Markov-Modulated Marked Hawkes Processes for Risk Prognosis

Ahmed Alaa, Scott Hu, Mihaela van der Schaar
ICML 2017 / Paper

2016

Balancing Suspense and Surprise: Timely Decision Making with Endogenous Information Acquisition

Ahmed Alaa, Mihaela van der Schaar
NeurIPS 2016 /  Paper

ForecastICU: A Prognostic Decision Support System for Timely Prediction of Intensive Care Unit Admission

Jinsung Yoon, Ahmed Alaa, Mihaela van der Schaar
ICML 2016 /  Paper