Ioana Bica

According to our database, Ioana Bica authored at least 27 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

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

CoRR, 2024

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., April, 2023

Neural Algorithmic Reasoning with Causal Regularisation.

Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic

Proceedings of the International Conference on Machine Learning, 2023

2022

DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction.

Yanke Li, Tobias Hatt, Ioana Bica, Mihaela van der Schaar

CoRR, 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

CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks.

David Buterez, Ioana Bica, Ifrah Tariq, Helena Andrés-Terré, Pietro Liò

Bioinform., 2022

Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data.

Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability.

Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation.

Ioana Bica, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

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

Model-Attentive Ensemble Learning for Sequence Modeling.

Victor D. Bourgin, Ioana Bica, Mihaela van der Schaar

CoRR, 2021

SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes.

Zhaozhi Qian, Yao Zhang, Ioana Bica, Angela M. Wood, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Time-series Generation by Contrastive Imitation.

Daniel Jarrett, Ioana Bica, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation.

Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar

Proceedings of the Neural Information Processing Systems Track on Datasets and Benchmarks 1, 2021

Invariant Causal Imitation Learning for Generalizable Policies.

Ioana Bica, Daniel Jarrett, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Clairvoyance: A Pipeline Toolkit for Medical Time Series.

Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning "What-if" Explanations for Sequential Decision-Making.

Ioana Bica, Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar

Proceedings of the 9th International Conference on Learning Representations, 2021

Learning Matching Representations for Individualized Organ Transplantation Allocation.

Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar

Proceedings of the 24th International Conference on Artificial Intelligence and Statistics, 2021

2020

ioanabica/COVID-19-Brazil: Code release.

Pedro Baqui, Ioana Bica, Valerio Marra, Ari Ercole, Mihaela van der Schaar

Dataset, June, 2020

Batch Inverse Reinforcement Learning Using Counterfactuals for Understanding Decision Making.

Ioana Bica, Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar

CoRR, 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

Proceedings of the Machine Learning for Health Workshop, 2020

Strictly Batch Imitation Learning by Energy-based Distribution Matching.

Daniel Jarrett, Ioana Bica, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks.

Ioana Bica, James Jordon, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

OrganITE: Optimal transplant donor organ offering using an individual treatment effect.

Jeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar

Proceedings of the 37th International Conference on Machine Learning, 2020

Estimating counterfactual treatment outcomes over time through adversarially balanced representations.

Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar

Proceedings of the 8th International Conference on Learning Representations, 2020

2018

Multi-omics data integration using cross-modal neural networks.

Ioana Bica, Petar Velickovic, Hui Xiao

Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018