Miruna Oprescu

According to our database, Miruna Oprescu authored at least 21 papers between 2017 and 2026.

Collaborative distances:

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

2026

Recovering Whole-Brain Causal Connectivity under Indirect Observation with Applications to Human EEG and fMRI.

Sangyoon Bae, Miruna Oprescu, David Keetae Park, Shinjae Yoo, Jiook Cha

CoRR, February, 2026

Causal Inference on Networks under Misspecified Exposure Mappings: A Partial Identification Framework.

Maresa Schröder, Miruna Oprescu, Stefan Feuerriegel, Nathan Kallus

CoRR, February, 2026

2025

Spatial Deconfounder: Interference-Aware Deconfounding for Spatial Causal Inference.

Ayush Khot, Miruna Oprescu, Maresa Schröder, Ai Kagawa, Xihaier Luo

CoRR, October, 2025

Efficient Adaptive Experimentation with Non-Compliance.

Miruna Oprescu, Brian M. Cho, Nathan Kallus

CoRR, May, 2025

GST-UNet: Spatiotemporal Causal Inference with Time-Varying Confounders.

Miruna Oprescu, David Keetae Park, Xihaier Luo, Shinjae Yoo, Nathan Kallus

CoRR, February, 2025

SCENT: Robust Spatiotemporal Learning for Continuous Scientific Data via Scalable Conditioned Neural Fields.

David Keetae Park, Xihaier Luo, Guang Zhao, Seungjun Lee, Miruna Oprescu, Shinjae Yoo

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Estimating Heterogeneous Treatment Effects by Combining Weak Instruments and Observational Data.

Miruna Oprescu, Nathan Kallus

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Efficient and Sharp Off-Policy Evaluation in Robust Markov Decision Processes.

Andrew Bennett, Nathan Kallus, Miruna Oprescu, Wen Sun, Kaiwen Wang

Proceedings of the Advances in Neural Information Processing Systems 37: Annual Conference on Neural Information Processing Systems 2024, 2024

Low-rank MDPs with Continuous Action Spaces.

Miruna Oprescu, Andrew Bennett, Nathan Kallus

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2024

2023

SubseasonalClimateUSA: A Dataset for Subseasonal Forecasting and Benchmarking.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

B-Learner: Quasi-Oracle Bounds on Heterogeneous Causal Effects Under Hidden Confounding.

Miruna Oprescu, Jacob Dorn, Marah Ghoummaid, Andrew Jesson, Nathan Kallus, Uri Shalit

Proceedings of the International Conference on Machine Learning, 2023

Robust and Agnostic Learning of Conditional Distributional Treatment Effects.

Nathan Kallus, Miruna Oprescu

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

Adaptive Bias Correction for Improved Subseasonal Forecasting.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Judah Cohen, Miruna Oprescu, Ernest Fraenkel, Lester Mackey

CoRR, 2022

2021

Learned Benchmarks for Subseasonal Forecasting.

Soukayna Mouatadid, Paulo Orenstein, Genevieve Flaspohler, Miruna Oprescu, Judah Cohen, Franklyn Wang, Sean Knight, Maria Geogdzhayeva, Sam Levang, Ernest Fraenkel, Lester Mackey

CoRR, 2021

Estimating the Long-Term Effects of Novel Treatments.

Keith Battocchi, Eleanor Dillon, Maggie Hei, Greg Lewis, Miruna Oprescu, Vasilis Syrgkanis

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

Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber.

Vasilis Syrgkanis, Greg Lewis, Miruna Oprescu, Maggie Hei, Keith Battocchi, Eleanor Dillon, Jing Pan, Yifeng Wu, Paul Lo, Huigang Chen, Totte Harinen, Jeong-Yoon Lee

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

Online Learning with Optimism and Delay.

Genevieve Flaspohler, Francesco Orabona, Judah Cohen, Soukayna Mouatadid, Miruna Oprescu, Paulo Orenstein, Lester Mackey

Proceedings of the 38th International Conference on Machine Learning, 2021

2019

Machine Learning Estimation of Heterogeneous Treatment Effects with Instruments.

Vasilis Syrgkanis, Victor Lei, Miruna Oprescu, Maggie Hei, Keith Battocchi, Greg Lewis

Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Orthogonal Random Forest for Causal Inference.

Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

Proceedings of the 36th International Conference on Machine Learning, 2019

2018

Orthogonal Random Forest for Heterogeneous Treatment Effect Estimation.

Miruna Oprescu, Vasilis Syrgkanis, Zhiwei Steven Wu

CoRR, 2018

2017

Flexible and Scalable Deep Learning with MMLSpark.

Mark Hamilton, Sudarshan Raghunathan, Akshaya Annavajhala, Danil Kirsanov, Eduardo de Leon, Eli Barzilay, Ilya Matiach, Joe Davison, Maureen Busch, Miruna Oprescu, Ratan Sur, Roope Astala, Tong Wen, ChangYoung Park

Proceedings of the 4th International Conference on Predictive Applications and APIs, 2017