Publications

(2021). BORE: Bayesian Optimization by Density-Ratio Estimation. In ICML2021. Accepted as Long Presentation (Awarded to Top 3% of Papers).

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(2020). BORE: Bayesian Optimization by Density-Ratio Estimation. In NeurIPS2020 Meta-Learn. Accepted as Contributed Talk (Awarded to Best 3 Papers).

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(2020). Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial Settings. In NeurIPS2020. Accepted as Spotlight Presentation (Awarded to Top 3% of Papers).

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(2020). Model-based Asynchronous Hyperparameter and Neural Architecture Search. Preprint.

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(2019). Variational Graph Convolutional Networks. In NeurIPS2019 Graph Representation Learning. Accepted as Outstanding Contribution Talk (Awarded to Best 3 Papers).

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(2018). Cycle-Consistent Adversarial Learning as Approximate Bayesian Inference. In ICML2018 Theoretical Foundations and Applications of Deep Generative Models. Accepted as Contributed Talk..

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