Petar Stojanov

According to our database, Petar Stojanov authored at least 11 papers between 2017 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2024

Gene Regulatory Network Inference in the Presence of Dropouts: a Causal View.

Haoyue Dai, Ignavier Ng, Gongxu Luo, Peter Spirtes, Petar Stojanov, Kun Zhang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Partial Identifiability for Domain Adaptation.

Lingjing Kong, Shaoan Xie, Weiran Yao, Yujia Zheng, Guangyi Chen, Petar Stojanov, Victor Akinwande, Kun Zhang

CoRR, 2023

2022

Towards More Efficient and Data-Driven Domain Adaptation.

Petar Stojanov

PhD thesis, 2022

Partial disentanglement for domain adaptation.

Lingjing Kong, Shaoan Xie, Weiran Yao, Yujia Zheng, Guangyi Chen, Petar Stojanov, Victor Akinwande, Kun Zhang

Proceedings of the International Conference on Machine Learning, 2022

2021

Unpaired data empowers association tests.

Mingming Gong, Peng Liu, Frank C. Sciurba, Petar Stojanov, Dacheng Tao, George C. Tseng, Kun Zhang, Kayhan Batmanghelich

Bioinform., 2021

Domain Adaptation with Invariant Representation Learning: What Transformations to Learn?

Petar Stojanov, Zijian Li, Mingming Gong, Ruichu Cai, Jaime G. Carbonell, Kun Zhang

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

2020

Domain Adaptation As a Problem of Inference on Graphical Models.

Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Clark Glymour

CoRR, 2020

Domain Adaptation as a Problem of Inference on Graphical Models.

Kun Zhang, Mingming Gong, Petar Stojanov, Biwei Huang, Qingsong Liu, Clark Glymour

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

2019

Data-Driven Approach to Multiple-Source Domain Adaptation.

Petar Stojanov, Mingming Gong, Jaime G. Carbonell, Kun Zhang

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

Low-Dimensional Density Ratio Estimation for Covariate Shift Correction.

Petar Stojanov, Mingming Gong, Jaime G. Carbonell, Kun Zhang

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2017

Reconstructing cancer drug response networks using multitask learning.

Matthew Ruffalo, Petar Stojanov, Venkata Krishna Pillutla, Rohan Varma, Ziv Bar-Joseph

BMC Syst. Biol., 2017