Publications

(2020). Synbols: Probing Learning Algorithms with Synthetic Datasets. Neural Information Processing Systems (NeurIPS 2020).

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(2020). Differentiable Causal Discovery from Interventional Data. Neural Information Processing Systems (NeurIPS 2020).

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(2020). Gradient-based Neural DAG Learning with Interventions. Causal Learning for Decision Making workshop, ICLR 2020.

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(2020). Embedding Propagation: Smoother Manifold for Few-Shot Classification. European Conference on Computer Vision (ECCV 2020).

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(2019). Interpretable genotype-to-phenotype classifiers with performance guarantees. Scientific reports.

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(2019). Deep learning for electromyographic hand gesture signal classification using transfer learning. IEEE Transactions on Neural Systems and Rehabilitation Engineering.

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(2017). Maximum margin interval trees. Neural Information Processing Systems (NIPS 2017).

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(2016). Large scale modeling of antimicrobial resistance with interpretable classifiers. Machine Learning for Health Workshop, NIPS.

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(2015). Greedy Biomarker Discovery in the Genome with Applications to Antimicrobial Resistance. Greed is Great Workshop, ICML.

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(2014). Learning interpretable models of phenotypes from whole genome sequences with the Set Covering Machine. Machine Learning in Computational Biology Workshop, NIPS.

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(2013). MHC-NP: predicting peptides naturally processed by the MHC. Journal of immunological methods.

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(2013). Accelerated Robust Point Cloud Registration in Natural Environments through Positive and Unlabeled Learning. Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence.

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