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MIT
- San Francisco, CA
- https://www.linkedin.com/in/shaynetobrien/
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generative-models Public
Annotated, understandable, and visually interpretable PyTorch implementations of: VAE, BIRVAE, NSGAN, MMGAN, WGAN, WGANGP, LSGAN, DRAGAN, BEGAN, RaGAN, InfoGAN, fGAN, FisherGAN
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coreference-resolution Public
Efficient and clean PyTorch reimplementation of "End-to-end Neural Coreference Resolution" (Lee et al., EMNLP 2017).
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explicit-gan-eval Public
Code for reproducing the results of "Evaluating Generative Adversarial Networks on Explicitly Parameterized Distributions" (O'Brien et al., NeurIPS 2018).
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numerical-methods Public
Methods in numerical analysis. Includes: Lagrange interpolation, Chebyshev polynomials for optimal node spacing, iterative techniques to solve linear systems (Gauss-Seidel, Jacobi, SOR), SVD, PCA, …
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machine-translation Public
Neural machine translation on the IWSLT-2016 dataset of Ted talks translated between German and English using sequence-to-sequence models with/without attention and beam search.
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language-modeling Public
Language modeling on the Penn Treebank (PTB) corpus using a trigram model with linear interpolation, a neural probabilistic language model, and a regularized LSTM.


