Volodymyr Kuleshov

Scaffolding genomes using synthetic long read clouds

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Audio super resolution using neural networks

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Teaching materials for the applied machine learning course at Cornell Tech (online edition)

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Lecture materials for Cornell CS5785 Applied Machine Learning (Fall 2022)

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Lecture notes on probabilistic graphical modeling, based on Stanford CS228 (work in progress!)

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Deep hybrid models: bridging discriminative and generative approaches https://cs.stanford.edu/~ermon/papers/uai2017_cr.pdf

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Implementations of popular deep learning models in Theano+Lasagne

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Machine-curated database of genetic disease and genome-wide association studies

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Neural variational inference and learning in undirected graphical models http://www.stanford.edu/~kuleshov/papers/nips2017.pdf

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A few basic online learning algorithms

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