104 citations · 209 across the 10 of their papers we have counts for
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cs.LG2018
Differentiable Antithetic Sampling for Variance Reduction in Stochastic Variational Inference
Mike Wu, Noah Goodman, Stefano Ermon
Stochastic optimization techniques are standard in variational inference algorithms. These methods estimate gradients by approximating expectations with independent Monte Carlo sam…
cs.LG2018
Zero Shot Learning for Code Education: Rubric Sampling with Deep Learning Inference
Mike Wu, Milan Mosse, Noah Goodman +1
In modern computer science education, massive open online courses (MOOCs) log thousands of hours of data about how students solve coding challenges. Being so rich in data, these pl…
cs.LG2018
Multimodal Generative Models for Scalable Weakly-Supervised Learning
Mike Wu, Noah Goodman
Multiple modalities often co-occur when describing natural phenomena. Learning a joint representation of these modalities should yield deeper and more useful representations. Previ…