Publications

Counterfactual Fairness by Combining Factual and Counterfactual Predictions

Neural Information Processing Systems (NeurIPS), 2024.

Preprint Project Code

Enhanced Controllability of Diffusion Models via Feature Disentanglement and Realism-Enhanced Sampling Methods

European Conference on Computer Vision (ECCV), 2024.

Preprint Project

Vertical Validation: Evaluating Implicit Generative Models for Graphs on Thin Support Regions

Uncertainty in Artificial Intelligence (UAI), 2024.

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Towards Characterizing Domain Counterfactuals For Invertible Latent Causal Models

International Conference on Learning Representations (ICLR), 2024.

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Benchmarking Algorithms for Federated Domain Generalization

International Conference on Learning Representations (ICLR) (Spotlight paper, 5% acceptance), 2024.

Preprint PDF Project Project

Towards Practical Non-Adversarial Distribution Matching

International Conference on Artificial Intelligence and Statistics (AISTATS), 2024.

Preprint PDF Project

Fault-Tolerant Vertical Federated Learning on Dynamic Networks

arXiv preprint, 2023.

Preprint Project

Towards Explaining Distribution Shifts

International Conference on Machine Learning (ICML), 2023.

Preprint PDF Project Code

StarCraftImage: A Dataset For Prototyping Spatial Reasoning Methods For Multi-Agent Environments

IEEE/CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023.

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Efficient Federated Domain Translation

International Conference on Learning Representations (ICLR), 2023.

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Cooperative Distribution Alignment via JSD Upper Bound

Neural Information Processing Systems (NeurIPS), 2022.

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Discrete Tree Flows via Tree-Structured Permutations

International Conference on Machine Learning (ICML), 2022.

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Towards Explaining Image-Based Distribution Shifts

CVPR Workshop on Vision Datasets Understanding, 2022.

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Iterative Alignment Flows

International Conference on Artificial Intelligence and Statistics (AISTATS), 2022.

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Shapley Explanation Networks

International Conference on Learning Representations (ICLR), 2021.

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Feature Shift Detection: Localizing Which Features Have Shifted via Conditional Distribution Tests

Neural Information Processing Systems (NeurIPS), 2020.

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Automated Dependence Plots

Uncertainty in Artificial Intelligence (UAI), 2020.

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On the (In)fidelity and Sensitivity of Explanations

Neural Information Processing Systems (NeurIPS), 2019.

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Deep Point Process Destructors

NeurIPS Workshop on Learning with Temporal Point Processes, 2019.

Project

Deep Density Destructors

International Conference on Machine Learning (ICML), 2018.

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Hyperparameter Selection under Localized Label Noise via Corrupt Validation

Learning with Limited Labeled Data (NeurIPS Workshop), 2017.

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A Review of Multivariate Distributions for Count Data Derived from the Poisson Distribution

Wiley Interdisciplinary Reviews: Computational Statistics, 2017.

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Square Root Graphical Models: Multivariate Generalizations of Univariate Exponential Families that Permit Positive Dependencies

International Conference on Machine Learning (ICML), 2016.

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Fixed-Length Poisson MRF: Adding Dependencies to the Multinomial

Neural Information Processing Systems (NeurIPS), 2015.

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Capturing Semantically Meaningful Word Dependencies with an Admixture of Poisson MRFs

Neural Information Processing Systems (NeurIPS), 2014.

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Summarization of Twitter Microblogs

Computer Journal, 2014.

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Admixture of Poisson MRFs: A Topic Model with Word Dependencies

International Conference on Machine Learning (ICML), 2014.

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Towards Undistorted and Noise-free Speech in an MRI Scanner: Correlation Subtraction Followed by Spectral Noise Gating

The Journal of the Acoustical Society of America, 2014.

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Comparing Twitter Summarization Algorithms for Multiple Post Summaries

IEEE International Conference on Social Computing (SocialCom), 2011.

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