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ORCIDIoana Bica
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2020 – today
- 2024
[c19]Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic:
Improving fine-grained understanding in image-text pre-training. ICML 2024- [i21]Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic:
Improving fine-grained understanding in image-text pre-training. CoRR abs/2401.09865 (2024) - [i20]Lucas Beyer, Andreas Steiner, André Susano Pinto, Alexander Kolesnikov, Xiao Wang, Daniel Salz, Maxim Neumann, Ibrahim Alabdulmohsin, Michael Tschannen, Emanuele Bugliarello, Thomas Unterthiner
, Daniel Keysers, Skanda Koppula, Fangyu Liu, Adam Grycner, Alexey A. Gritsenko, Neil Houlsby, Manoj Kumar, Keran Rong, Julian Eisenschlos, Rishabh Kabra, Matthias Bauer, Matko Bosnjak, Xi Chen, Matthias Minderer, Paul Voigtlaender, Ioana Bica, Ivana Balazevic, Joan Puigcerver, Pinelopi Papalampidi, Olivier J. Hénaff, Xi Xiong, Radu Soricut, Jeremiah Harmsen, Xiaohua Zhai:
PaliGemma: A versatile 3B VLM for transfer. CoRR abs/2407.07726 (2024) - 2023
- [j2]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) - [c18]Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic:
Neural Algorithmic Reasoning with Causal Regularisation. ICML 2023: 2272-2288 - [i19]Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic:
Neural Algorithmic Reasoning with Causal Regularisation. CoRR abs/2302.10258 (2023) - [i18]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) - [i17]Daniel Jarrett, Ioana Bica, Mihaela van der Schaar:
Time-series Generation by Contrastive Imitation. CoRR abs/2311.01388 (2023) - [i16]Ioana Bica, Daniel Jarrett, Mihaela van der Schaar:
Invariant Causal Imitation Learning for Generalizable Policies. CoRR abs/2311.01489 (2023) - 2022
- [j1]David Buterez, Ioana Bica, Ifrah Tariq, Helena Andrés-Terré, Pietro Liò:
CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. Bioinform. 38(5): 1277-1286 (2022) - [c17]Ioana Bica, Mihaela van der Schaar:
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. NeurIPS 2022 - [c16]Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar:
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. NeurIPS 2022 - [c15]Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar:
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. NeurIPS 2022 - [i15]Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic:
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet? CoRR abs/2201.05119 (2022) - [i14]Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar:
Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. CoRR abs/2206.08363 (2022) - [i13]Yanke Li, Tobias Hatt, Ioana Bica, Mihaela van der Schaar:
DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction. CoRR abs/2208.01373 (2022) - [i12]Ioana Bica, Mihaela van der Schaar:
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. CoRR abs/2210.06183 (2022) - [i11]Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar:
Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. CoRR abs/2210.13043 (2022) - 2021
- [c14]Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar:
Learning Matching Representations for Individualized Organ Transplantation Allocation. AISTATS 2021: 2134-2142 - [c13]Ioana Bica, Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar:
Learning "What-if" Explanations for Sequential Decision-Making. ICLR 2021 - [c12]Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar:
Clairvoyance: A Pipeline Toolkit for Medical Time Series. ICLR 2021 - [c11]Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar:
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. NeurIPS Datasets and Benchmarks 2021 - [c10]Zhaozhi Qian, Yao Zhang, Ioana Bica, Angela M. Wood, Mihaela van der Schaar:
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes. NeurIPS 2021: 3178-3190 - [c9]Ioana Bica, Daniel Jarrett, Mihaela van der Schaar:
Invariant Causal Imitation Learning for Generalizable Policies. NeurIPS 2021: 3952-3964 - [c8]Daniel Jarrett, Ioana Bica, Mihaela van der Schaar:
Time-series Generation by Contrastive Imitation. NeurIPS 2021: 28968-28982 - [i10]Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar:
Learning Matching Representations for Individualized Organ Transplantation Allocation. CoRR abs/2101.11769 (2021) - [i9]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) - [i8]Victor D. Bourgin, Ioana Bica, Mihaela van der Schaar:
Model-Attentive Ensemble Learning for Sequence Modeling. CoRR abs/2102.11500 (2021) - [i7]Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar:
The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. CoRR abs/2106.04240 (2021) - [i6]Jeroen Berrevoets, Alicia Curth, Ioana Bica, Eoin F. McKinney, Mihaela van der Schaar:
Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time. CoRR abs/2112.03811 (2021) - 2020
- [c7]Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar:
Estimating counterfactual treatment outcomes over time through adversarially balanced representations. ICLR 2020 - [c6]Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar:
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. ICML 2020: 884-895 - [c5]Jeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar:
OrganITE: Optimal transplant donor organ offering using an individual treatment effect. NeurIPS 2020 - [c4]Ioana Bica, James Jordon, Mihaela van der Schaar:
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. NeurIPS 2020 - [c3]Daniel Jarrett, Ioana Bica, Mihaela van der Schaar:
Strictly Batch Imitation Learning by Energy-based Distribution Matching. NeurIPS 2020 - [c2]Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland:
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. ML4H@NeurIPS 2020: 1-11 - [d1]Pedro Baqui, Ioana Bica, Valerio Marra, Ari Ercole, Mihaela van der Schaar:
ioanabica/COVID-19-Brazil: Code release. Zenodo, 2020
- [i5]Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar:
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations. CoRR abs/2002.04083 (2020) - [i4]Ioana Bica, James Jordon, Mihaela van der Schaar:
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. CoRR abs/2002.12326 (2020) - [i3]Daniel Jarrett, Ioana Bica, Mihaela van der Schaar:
Strictly Batch Imitation Learning by Energy-based Distribution Matching. CoRR abs/2006.14154 (2020) - [i2]Ioana Bica, Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar:
Batch Inverse Reinforcement Learning Using Counterfactuals for Understanding Decision Making. CoRR abs/2007.13531 (2020)
2010 – 2019
- 2019
- [i1]Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar:
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. CoRR abs/1902.00450 (2019) - 2018
- [c1]Ioana Bica, Petar Velickovic, Hui Xiao:
Multi-omics data integration using cross-modal neural networks. ESANN 2018
Coauthor Index
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