Ioana Bica - RankMe

42 papers A* 15A 1B 1Journal 23Unranked 2

Year	Rank	Type	Title / Venue / Authors
2024	A*	`conf`	Improving fine-grained understanding in image-text pre-training. ICML Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic
2024	J	`jnl`	Improving fine-grained understanding in image-text pre-training. CoRR Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bosnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic
2024	J	`jnl`	PaliGemma: A versatile 3B VLM for transfer. CoRR 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
2023	J	`jnl`	Clairvoyance: A Pipeline Toolkit for Medical Time Series. CoRR Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
2023	J	`jnl`	Invariant Causal Imitation Learning for Generalizable Policies. CoRR Ioana Bica, Daniel Jarrett, Mihaela van der Schaar
2023	A*	`conf`	Neural Algorithmic Reasoning with Causal Regularisation. ICML Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic
2023	J	`jnl`	Neural Algorithmic Reasoning with Causal Regularisation. CoRR Beatrice Bevilacqua, Kyriacos Nikiforou, Borja Ibarz, Ioana Bica, Michela Paganini, Charles Blundell, Jovana Mitrovic, Petar Velickovic
2023	J	`jnl`	Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. ACM Trans. Comput. Heal. Trent Kyono, Ioana Bica, Zhaozhi Qian, Mihaela van der Schaar
2023	J	`jnl`	Time-series Generation by Contrastive Imitation. CoRR Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
2022	A*	`conf`	Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. NeurIPS Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
2022	J	`jnl`	Benchmarking Heterogeneous Treatment Effect Models through the Lens of Interpretability. CoRR Jonathan Crabbé, Alicia Curth, Ioana Bica, Mihaela van der Schaar
2022	J	`jnl`	CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. Bioinform. David Buterez, Ioana Bica, Ifrah Tariq, Helena Andrés-Terré, Pietro Liò
2022	J	`jnl`	DAPDAG: Domain Adaptation via Perturbed DAG Reconstruction. CoRR Yanke Li, Tobias Hatt, Ioana Bica, Mihaela van der Schaar
2022	A*	`conf`	Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. NeurIPS Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
2022	J	`jnl`	Data-IQ: Characterizing subgroups with heterogeneous outcomes in tabular data. CoRR Nabeel Seedat, Jonathan Crabbé, Ioana Bica, Mihaela van der Schaar
2022	J	`jnl`	Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet? CoRR Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic
2022	A*	`conf`	Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. NeurIPS Ioana Bica, Mihaela van der Schaar
2022	J	`jnl`	Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation. CoRR Ioana Bica, Mihaela van der Schaar
2021	A*	`conf`	Clairvoyance: A Pipeline Toolkit for Medical Time Series. ICLR Daniel Jarrett, Jinsung Yoon, Ioana Bica, Zhaozhi Qian, Ari Ercole, Mihaela van der Schaar
2021	J	`jnl`	Disentangled Counterfactual Recurrent Networks for Treatment Effect Inference over Time. CoRR Jeroen Berrevoets, Alicia Curth, Ioana Bica, Eoin F. McKinney, Mihaela van der Schaar
2021	A*	`conf`	Invariant Causal Imitation Learning for Generalizable Policies. NeurIPS Ioana Bica, Daniel Jarrett, Mihaela van der Schaar
2021	A*	`conf`	Learning "What-if" Explanations for Sequential Decision-Making. ICLR Ioana Bica, Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
2021	A	`conf`	Learning Matching Representations for Individualized Organ Transplantation Allocation. AISTATS Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar
2021	J	`jnl`	Learning Matching Representations for Individualized Organ Transplantation Allocation. CoRR Can Xu, Ahmed M. Alaa, Ioana Bica, Brent D. Ershoff, Maxime Cannesson, Mihaela van der Schaar
2021	J	`jnl`	Model-Attentive Ensemble Learning for Sequence Modeling. CoRR Victor D. Bourgin, Ioana Bica, Mihaela van der Schaar
2021	J	`jnl`	Selecting Treatment Effects Models for Domain Adaptation Using Causal Knowledge. CoRR Trent Kyono, Ioana Bica, Zhaozhi Qian, Mihaela van der Schaar
2021	A*	`conf`	SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes. NeurIPS Zhaozhi Qian, Yao Zhang, Ioana Bica, Angela M. Wood, Mihaela van der Schaar
2021	—	`conf`	The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. NeurIPS Datasets and Benchmarks Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
2021	J	`jnl`	The Medkit-Learn(ing) Environment: Medical Decision Modelling through Simulation. CoRR Alex J. Chan, Ioana Bica, Alihan Hüyük, Daniel Jarrett, Mihaela van der Schaar
2021	A*	`conf`	Time-series Generation by Contrastive Imitation. NeurIPS Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
2020	J	`jnl`	Batch Inverse Reinforcement Learning Using Counterfactuals for Understanding Decision Making. CoRR Ioana Bica, Daniel Jarrett, Alihan Hüyük, Mihaela van der Schaar
2020	J	`jnl`	Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations. CoRR Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar
2020	A*	`conf`	Estimating counterfactual treatment outcomes over time through adversarially balanced representations. ICLR Ioana Bica, Ahmed M. Alaa, James Jordon, Mihaela van der Schaar
2020	A*	`conf`	Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. NeurIPS Ioana Bica, James Jordon, Mihaela van der Schaar
2020	J	`jnl`	Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks. CoRR Ioana Bica, James Jordon, Mihaela van der Schaar
2020	—	`conf`	Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All. ML4H@NeurIPS Suproteem K. Sarkar, Subhrajit Roy, Emily Alsentzer, Matthew B. A. McDermott, Fabian Falck, Ioana Bica, Griffin Adams, Stephen Pfohl, Stephanie L. Hyland
2020	A*	`conf`	OrganITE: Optimal transplant donor organ offering using an individual treatment effect. NeurIPS Jeroen Berrevoets, James Jordon, Ioana Bica, Alexander Gimson, Mihaela van der Schaar
2020	A*	`conf`	Strictly Batch Imitation Learning by Energy-based Distribution Matching. NeurIPS Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
2020	J	`jnl`	Strictly Batch Imitation Learning by Energy-based Distribution Matching. CoRR Daniel Jarrett, Ioana Bica, Mihaela van der Schaar
2020	A*	`conf`	Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. ICML Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar
2019	J	`jnl`	Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders. CoRR Ioana Bica, Ahmed M. Alaa, Mihaela van der Schaar
2018	B	`conf`	Multi-omics data integration using cross-modal neural networks. ESANN Ioana Bica, Petar Velickovic, Hui Xiao