Multi-omics data integration using cross-modal neural networks. - Ioana Bica; Petar Velickovic; Hui Xiao (ESANN, 2018)

Estimating counterfactual treatment outcomes over time through adversarially balanced representations. - Ioana Bica; Ahmed M. Alaa; James Jordon; Mihaela van der Schaar (ICLR, 2020)

Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. - Ioana Bica; Ahmed M. Alaa; Mihaela van der Schaar (ICML, 2020)

OrganITE: Optimal transplant donor organ offering using an individual treatment effect. - Jeroen Berrevoets; James Jordon; Ioana Bica; Alexander Gimson; Mihaela van der Schaar (NeurIPS, 2020)

Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. - Ioana Bica; James Jordon; Mihaela van der Schaar (NeurIPS, 2020)

Strictly Batch Imitation Learning by Energy-based Distribution Matching. - Daniel Jarrett; Ioana Bica; Mihaela van der Schaar (NeurIPS, 2020)

Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. - Suproteem K. Sarkar; Subhrajit Roy; Emily Alsentzer; Matthew B. A. McDermott; Fabian Falck; Ioana Bica; Griffin Adams; Stephen Pfohl; Stephanie L. Hyland (ML4H@NeurIPS, 2020)

Batch Inverse Reinforcement Learning Using Counterfactuals for Understanding Decision Making. - Ioana Bica; Daniel Jarrett; Alihan Hüyük; Mihaela van der Schaar (CoRR, 2020)

ioanabica/COVID-19-Brazil: Code release. - Pedro Baqui; Ioana Bica; Valerio Marra; Ari Ercole; Mihaela van der Schaar (Zenodo, 2020)

Learning Matching Representations for Individualized Organ Transplantation Allocation. - Can Xu; Ahmed M. Alaa; Ioana Bica; Brent D. Ershoff; Maxime Cannesson; Mihaela van der Schaar (AISTATS, 2021)

Learning "What-if" Explanations for Sequential Decision-Making. - Ioana Bica; Daniel Jarrett; Alihan Hüyük; Mihaela van der Schaar (ICLR, 2021)

Clairvoyance: A Pipeline Toolkit for Medical Time Series. - Daniel Jarrett; Jinsung Yoon; Ioana Bica; Zhaozhi Qian; Ari Ercole; Mihaela van der Schaar (ICLR, 2021)

Invariant Causal Imitation Learning for Generalizable Policies. - Ioana Bica; Daniel Jarrett; Mihaela van der Schaar (NeurIPS, 2021)

The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. - Alex J. Chan; Ioana Bica; Alihan Hüyük; Daniel Jarrett; Mihaela van der Schaar (NeurIPS Datasets and Benchmarks, 2021)

Time-series Generation by Contrastive Imitation. - Daniel Jarrett; Ioana Bica; Mihaela van der Schaar (NeurIPS, 2021)

SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes. - Zhaozhi Qian; Yao Zhang; Ioana Bica; Angela M. Wood; Mihaela van der Schaar (NeurIPS, 2021)

Model-Attentive Ensemble Learning for Sequence Modeling. - Victor D. Bourgin; Ioana Bica; Mihaela van der Schaar (CoRR, 2021)

Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time. - Jeroen Berrevoets; Alicia Curth; Ioana Bica; Eoin F. McKinney; Mihaela van der Schaar (CoRR, 2021)

Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. - Ioana Bica; Mihaela van der Schaar (NeurIPS, 2022)

Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. - Jonathan Crabbé; Alicia Curth; Ioana Bica; Mihaela van der Schaar (NeurIPS, 2022)

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. - Nabeel Seedat; Jonathan Crabbé; Ioana Bica; Mihaela van der Schaar (NeurIPS, 2022)

CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. - David Buterez; Ioana Bica; Ifrah Tariq; Helena Andrés-Terré; Pietro Liò (Bioinform., 2022)

Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet? - Nenad Tomasev; Ioana Bica; Brian McWilliams; Lars Buesing; Razvan Pascanu; Charles Blundell; Jovana Mitrovic (CoRR, 2022)

DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction. - Yanke Li; Tobias Hatt; Ioana Bica; Mihaela van der Schaar (CoRR, 2022)

Neural Algorithmic Reasoning with Causal Regularisation. - Beatrice Bevilacqua; Kyriacos Nikiforou; Borja Ibarz; Ioana Bica; Michela Paganini; Charles Blundell; Jovana Mitrovic; Petar Velickovic (ICML, 2023)

Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. - Trent Kyono; Ioana Bica; Zhaozhi Qian; Mihaela van der Schaar (ACM Trans. Comput. Heal., 2023)

Improving fine-grained understanding in image-text pre-training. - Ioana Bica; Anastasija Ilic; Matthias Bauer; Goker Erdogan; Matko Bosnjak; Christos Kaplanis; Alexey A. Gritsenko; Matthias Minderer; Charles Blundell; Razvan Pascanu; Jovana Mitrovic (ICML, 2024)

PaliGemma: A versatile 3B VLM for transfer. - Lucas Beyer; Andreas Steiner 001; André Susano Pinto; Alexander Kolesnikov 003; Xiao Wang 038; Daniel Salz; Maxim Neumann; Ibrahim Alabdulmohsin; Michael Tschannen; Emanuele Bugliarello; Thomas Unterthiner; Daniel Keysers; et al. (CoRR, 2024)