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Ioana Bica
Observed name:
Bica, Ioana
Observed institutions:
Turing Institute,
Purdue University West Lafayette,
University of Cambridge,
University of Oxford,
Google DeepMind (United Kingdom),
The Alan Turing Institute
show all 6
ORCID:
0000-0001-5564-0214
Observed ORCID:
0000-0001-5564-0214
OpenAlex ID:
A5006610847
Ethnic and regional variations in hospital mortality from COVID-19 in Brazil: a cross-sectional observational study
2020
·
Pedro Baqui
, Ioana Bica
, et al.
·
The Lancet Global Health
·
632
PDF
From Real‐World Patient Data to Individualized Treatment Effects Using Machine Learning: Current and Future Methods to Address Underlying Challenges
2020
·
Ioana Bica
, Ahmed M. Alaa
, et al.
·
Clinical Pharmacology & Therapeutics
·
207
PDF
Machine learning for clinical trials in the era of COVID-19
2020
·
William R. Zame
, Ioana Bica
, et al.
·
Statistics in Biopharmaceutical Research
·
67
PDF
Comparing COVID-19 risk factors in Brazil using machine learning: the importance of socioeconomic, demographic and structural factors
2021
·
Pedro Baqui
, Valerio Marra
, et al.
·
Scientific Reports
·
57
PDF
Estimating Counterfactual Treatment Outcomes over Time Through Adversarially Balanced Representations
2020
·
Bica, Ioana
, Alaa, Ahmed M.
, et al.
·
arXiv (Cornell University)
·
53
PDF
Estimating the Effects of Continuous-valued Interventions using Generative Adversarial Networks
2020
·
Bica, Ioana
, Jordon, James
, et al.
·
arXiv (Cornell University)
·
51
PDF
CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks
2021
·
David Buterez
, Ioana Bica
, et al.
·
Bioinformatics
·
44
PDF
Time Series Deconfounder: Estimating Treatment Effects over Time in the Presence of Hidden Confounders
2019
·
Bica, Ioana
, Alaa, Ahmed M.
, et al.
·
arXiv (Cornell University)
·
28
PDF
Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet?
2022
·
Tomasev, Nenad
, Bica, Ioana
, et al.
·
arXiv (Cornell University)
·
22
PDF
Unsupervised generative and graph representation learning for modelling cell differentiation
2020
·
Ioana Bica
, Helena Andrés-Terré
, et al.
·
Scientific Reports
·
20
PDF
Clairvoyance: A Pipeline Toolkit for Medical Time Series
2021
·
Jarrett, Daniel
, Yoon, Jinsung
, et al.
·
arXiv (Cornell University)
·
18
PDF
PaliGemma: A versatile 3B VLM for transfer
2024
·
Beyer, Lucas
, Steiner, Andreas
, et al.
·
arXiv (Cornell University)
·
17
PDF
Strictly Batch Imitation Learning by Energy-based Distribution Matching
2020
·
Jarrett, Daniel
, Bica, Ioana
, et al.
·
arXiv (Cornell University)
·
17
PDF
OrganITE: Optimal transplant donor organ offering using an individual treatment effect
2020
·
Jeroen Berrevoets
, James Jordon
, et al.
·
Lirias
·
14
PDF
Data-IQ: Characterizing Subgroups with Heterogeneous Outcomes in Tabular Data
2022
·
Nabeel Seedat
, Jonathan Crabbé
, et al.
·
neural information processing systems
·
12
PDF
Feature importance in multi-dimensional tissue-engineering datasets: Random forest assisted optimization of experimental variables for collagen scaffolds
2021
·
Malavika Nair
, Ioana Bica
, et al.
·
Applied Physics Reviews
·
12
Invariant Causal Imitation Learning for Generalizable Policies
2023
·
Bica, Ioana
, Jarrett, Daniel
, et al.
·
arXiv (Cornell University)
·
11
PDF
Time-series Generation by Contrastive Imitation
2023
·
Jarrett, Daniel
, Bica, Ioana
, et al.
·
arXiv (Cornell University)
·
10
PDF
Transfer Learning on Heterogeneous Feature Spaces for Treatment Effects Estimation
2022
·
Ioana Bica
, Mihaela Van Der Schaar
·
neural information processing systems
·
10
PDF
SyncTwin: Treatment Effect Estimation with Longitudinal Outcomes
2021
·
Zhaozhi Qian
, Yao Zhang
, et al.
·
neural information processing systems
·
10
Multi-omics data integration using cross-modal neural networks.
2018
·
Ioana Bica
, Petar Veličković
, et al.
·
The European Symposium on Artificial Neural Networks
·
9
Machine Learning for Health (ML4H) 2020: Advancing Healthcare for All
2020
·
Suproteem K. Sarkar
, Subhrajit Roy
, et al.
·
8
Benchmarking Heterogeneous Treatment Effect Models Through the Lens of Interpretability
2022
·
Jonathan Crabbé
, Alicia Curth
, et al.
·
neural information processing systems
·
7
PDF
Learning "What-if" Explanations for Sequential Decision-Making
2020
·
Bica, Ioana
, Jarrett, Daniel
, et al.
·
arXiv (Cornell University)
·
7
PDF
Improving fine-grained understanding in image-text pre-training
2024
·
Bica, Ioana
, Ilić, Anastasija
, et al.
·
arXiv (Cornell University)
·
4
PDF
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Works count:
46
Citation count:
1,439
H-index:
14
I10-index:
21
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