Bayesian Markov Blanket Estimation. - Dinu Kaufmann; Sonali Parbhoo; Aleksander Wieczorek; Sebastian Keller 001; David Adametz; Volker Roth 001 (AISTATS, 2016)

Combining Kernel and Model Based Learning for HIV Therapy Selection. - Sonali Parbhoo; Jasmina Bogojeska; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (CRI, 2017)

Beyond Sparsity: Tree Regularization of Deep Models for Interpretability. - Mike Wu; Michael C. Hughes; Sonali Parbhoo; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (AAAI, 2018)

Causal Deep Information Bottleneck. - Sonali Parbhoo; Mario Wieser; Volker Roth 001 (CoRR, 2018)

Informed MCMC with Bayesian Neural Networks for Facial Image Analysis. - Adam Kortylewski; Mario Wieser; Andreas Morel-Forster; Aleksander Wieczorek; Sonali Parbhoo; Volker Roth 001; Thomas Vetter (CoRR, 2018)

Estimating Causal Effects With Partial Covariates For Clinical Interpretability. - Sonali Parbhoo; Mario Wieser; Volker Roth 001 (CoRR, 2018)

Greedy Structure Learning of Hierarchical Compositional Models. - Adam Kortylewski; Aleksander Wieczorek; Mario Wieser; Clemens Blumer; Sonali Parbhoo; Andreas Morel-Forster; Volker Roth 001; Thomas Vetter (CVPR, 2019)

Regional Tree Regularization for Interpretability in Black Box Models. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Ryan Kindle; Leo A. Celi; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (CoRR, 2019)

Regional Tree Regularization for Interpretability in Deep Neural Networks. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Ryan Kindle; Leo A. Celi; Maurizio Zazzi; Volker Roth 001; Finale Doshi-Velez (AAAI, 2020)

Interpretable Off-Policy Evaluation in Reinforcement Learning by Highlighting Influential Transitions. - Omer Gottesman; Joseph Futoma; Yao Liu 009; Sonali Parbhoo; Leo A. Celi; Emma Brunskill; Finale Doshi-Velez (ICML, 2020)

Transfer Learning from Well-Curated to Less-Resourced Populations with HIV. - Sonali Parbhoo; Mario Wieser; Volker Roth 001; Finale Doshi-Velez (MLHC, 2020)

Inverse Learning of Symmetries. - Mario Wieser; Sonali Parbhoo; Aleksander Wieczorek; Volker Roth 001 (NeurIPS, 2020)

Inverse Learning of Symmetry Transformations. - Mario Wieser; Sonali Parbhoo; Aleksander Wieczorek; Volker Roth 001 (CoRR, 2020)

Real-time Prediction of COVID-19 related Mortality using Electronic Health Records. - Patrick Schwab; Arash Mehrjou; Sonali Parbhoo; Leo Anthony Celi; Jürgen Hetzel; Markus Hofer; Bernhard Schölkopf; Stefan Bauer (CoRR, 2020)

Information Bottleneck for Estimating Treatment Effects with Systematically Missing Covariates. - Sonali Parbhoo; Mario Wieser; Aleksander Wieczorek; Volker Roth 001 (Entropy, 2020)

Learning Predictive and Interpretable Timeseries Summaries from ICU Data. - Nari Johnson; Sonali Parbhoo; Andrew Slavin Ross; Finale Doshi-Velez (AMIA, 2021)

Learning Conditional Invariance Through Cycle Consistency. - Maxim Samarin; Vitali Nesterov; Mario Wieser; Aleksander Wieczorek; Sonali Parbhoo; Volker Roth 001 (GCPR, 2021)

Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible. - Melanie F. Pradier; Javier Zazo; Sonali Parbhoo; Roy H. Perlis; Maurizio Zazzi; Finale Doshi-Velez (CoRR, 2021)

NCoRE: Neural Counterfactual Representation Learning for Combinations of Treatments. - Sonali Parbhoo; Stefan Bauer; Patrick Schwab (CoRR, 2021)

Pre-emptive learning-to-defer for sequential medical decision-making under uncertainty. - Shalmali Joshi; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2021)

On Learning Prediction-Focused Mixtures. - Abhishek Sharma; Catherine Zeng; Sanjana Narayanan; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2021)

Optimizing for Interpretability in Deep Neural Networks with Tree Regularization. - Mike Wu; Sonali Parbhoo; Michael C. Hughes; Volker Roth 001; Finale Doshi-Velez (J. Artif. Intell. Res., 2021)

Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. - Carissa Wu; Sonali Parbhoo; Marton Havasi; Finale Doshi-Velez (MLHC, 2022)

Addressing Leakage in Concept Bottleneck Models. - Marton Havasi; Sonali Parbhoo; Finale Doshi-Velez (NeurIPS, 2022)

Generalizing Off-Policy Evaluation From a Causal Perspective For Sequential Decision-Making. - Sonali Parbhoo; Shalmali Joshi; Finale Doshi-Velez (CoRR, 2022)

Policy Optimization with Sparse Global Contrastive Explanations. - Jiayu Yao; Sonali Parbhoo; Weiwei Pan; Finale Doshi-Velez (CoRR, 2022)

Adaptive Experimental Design for Intrusion Data Collection. - Kate Highnam; Zach Hanif; Ellie Van Vogt; Sonali Parbhoo; Sergio Maffeis; Nicholas R. Jennings (CAMLIS, 2023)

The Unintended Consequences of Discount Regularization: Improving Regularization in Certainty Equivalence Reinforcement Learning. - Sarah Rathnam; Sonali Parbhoo; Weiwei Pan; Susan A. Murphy; Finale Doshi-Velez (ICML, 2023)

Which Explanation Makes Sense? A Critical Evaluation of Local Explanations for Assessing Cervical Cancer Risk. - Célia Wafa Ayad; Thomas Bonnier; Benjamin Bosch; Jesse Read; Sonali Parbhoo (MLHC, 2023)

Robust Decision-Focused Learning for Reward Transfer. - Abhishek Sharma; Sonali Parbhoo; Omer Gottesman; Finale Doshi-Velez (CoRR, 2023)

Leveraging Factored Action Spaces for Off-Policy Evaluation. - Aaman Rebello; Shengpu Tang; Jenna Wiens; Sonali Parbhoo (CoRR, 2023)

Bayesian Inverse Transition Learning for Offline Settings. - Leo Benac; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2023)

Learning-to-defer for sequential medical decision-making under uncertainty. - Shalmali Joshi; Sonali Parbhoo; Finale Doshi-Velez (Trans. Mach. Learn. Res., 2023)

Risk Sensitive Dead-end Identification in Safety-Critical Offline Reinforcement Learning. - Taylor W. Killian; Sonali Parbhoo; Marzyeh Ghassemi (Trans. Mach. Learn. Res., 2023)

Decision-Focused Model-based Reinforcement Learning for Reward Transfer. - Abhishek Sharma; Sonali Parbhoo; Omer Gottesman; Finale Doshi-Velez (MLHC, 2024)

Guarantee Regions for Local Explanations. - Marton Havasi; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2024)

Towards Integrating Personal Knowledge into Test-Time Predictions. - Isaac Lage; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2024)

Tree-Based Leakage Inspection and Control in Concept Bottleneck Models. - Angelos Ragkousis; Sonali Parbhoo (CoRR, 2024)

Insights from the Inverse: Reconstructing LLM Training Goals Through Inverse RL. - Jared Joselowitz; Arjun Jagota; Satyapriya Krishna; Sonali Parbhoo (CoRR, 2024)

Inverse Transition Learning: Learning Dynamics from Demonstrations. - Leo Benac; Abhishek Sharma; Sonali Parbhoo; Finale Doshi-Velez (CoRR, 2024)

Concept-driven Off Policy Evaluation. - Ritam Majumdar; Jack Teversham; Sonali Parbhoo (CoRR, 2024)

Rethinking Discount Regularization: New Interpretations, Unintended Consequences, and Solutions for Regularization in Reinforcement Learning. - Sarah Rathnam; Sonali Parbhoo; Siddharth Swaroop; Weiwei Pan; Susan A. Murphy; Finale Doshi-Velez (J. Mach. Learn. Res., 2024)

Task-Relevant Feature Selection with Prediction Focused Mixture Models. - Abhishek Sharma; Catherine Zeng; Sanjana Narayanan; Sonali Parbhoo; Roy H. Perlis; Finale Doshi-Velez (Trans. Mach. Learn. Res., 2024)

Do Regularization Methods for Shortcut Mitigation Work As Intended? - Haoyang Hong; Ioanna Papanikolaou; Sonali Parbhoo (AISTATS, 2025)

Decision-Point Guided Safe Policy Improvement. - Abhishek Sharma; Leo Benac; Sonali Parbhoo; Finale Doshi-Velez (AISTATS, 2025)

User Studies in Human-Feature-Integration. - Yixin Li; Lucas Lefebvre; Sonali Parbhoo; Finale Doshi-Velez; Isaac Lage (IUI Workshops, 2025)

Feature Importance Depends on Properties of the Data: Towards Choosing the Correct Explanations for Your Data and Decision Trees based Models. - Célia Wafa Ayad; Thomas Bonnier; Benjamin Bosch; Sonali Parbhoo; Jesse Read (CoRR, 2025)

Causal Bayesian Optimization with Unknown Graphs. - Jean Durand; Yashas Annadani; Stefan Bauer; Sonali Parbhoo (CoRR, 2025)

Improving ARDS Diagnosis Through Context-Aware Concept Bottleneck Models. - Anish Narain; Ritam Majumdar; Nikita Narayanan; Dominic Marshall; Sonali Parbhoo (CoRR, 2025)