(2024). Privacy-Constrained Policies via Mutual Information Regularized Policy Gradients. AAAI.


(2022). LMPriors: Pre-Trained Language Models as Task-Specific Priors. First Workshop on Foundation Models for Decision Making, Neurips 2022.

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(2021). Scalable Variational Approaches for Bayesian Causal Discovery. Neural Information Processing Systems (NeurIPS).

(2021). IQ-Learn: Inverse soft-Q Learning for Imitation. Neural Information Processing Systems (NeurIPS).


(2020). Flexible Approximate Inference via Stratified Normalizing Flows. Conference on Uncertainty in Artificial Intelligence (UAI).


(2018). Parallelizing linear recurrent neural nets over sequence length. International Conference on Learning Representations (ICLR).

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(2018). Exploring hierarchy-aware inverse reinforcement learning. First Workshop on Goal Specifications for Reinforcement Learning, ICML 2018.


(2017). Investigating Variational Gaussian Process State-Space Models. Master’s Thesis.


(2015). Simulation of plants in buildings; incorporating plant-Air interactions in building energy simulation. 14th International Conference of IBPSA-Building Simulation 2015, BS 2015, Conference Proceedings.