30 citations · 30 across the 2 of their papers we have counts for
3 papers
State-Reification Networks: Improving Generalization by Modeling the Distribution of Hidden Representations
Alex Lamb, Jonathan Binas, Anirudh Goyal +5
Machine learning promises methods that generalize well from finite labeled data. However, the brittleness of existing neural net approaches is revealed by notable failures, such as…
State-Denoised Recurrent Neural Networks
Michael C. Mozer, Denis Kazakov, Robert V. Lindsey
Recurrent neural networks (RNNs) are difficult to train on sequence processing tasks, not only because input noise may be amplified through feedback, but also because any inaccurac…
Discrete Event, Continuous Time RNNs
Michael C. Mozer, Denis Kazakov, Robert V. Lindsey
We investigate recurrent neural network architectures for event-sequence processing. Event sequences, characterized by discrete observations stamped with continuous-valued times of…