18 citations · 24 across the 7 of their papers we have counts for
9 papers
Conjugate Energy-Based Models
Hao Wu, Babak Esmaeili, Michael Wick +2
In this paper, we propose conjugate energy-based models (CEBMs), a new class of energy-based models that define a joint density over data and latent variables. The joint density of…
Detecting and Exorcising Statistical Demons from Language Models with Anti-Models of Negative Data
Michael L. Wick, Kate Silverstein, Jean-Baptiste Tristan +2
It's been said that "Language Models are Unsupervised Multitask Learners." Indeed, self-supervised language models trained on "positive" examples of English text generalize in desi…
Verification of ML Systems via Reparameterization
Jean-Baptiste Tristan, Joseph Tassarotti, Koundinya Vajjha +2
As machine learning is increasingly used in essential systems, it is important to reduce or eliminate the incidence of serious bugs. A growing body of research has developed machin…
Sketching for Latent Dirichlet-Categorical Models
Joseph Tassarotti, Jean-Baptiste Tristan, Michael Wick
Recent work has explored transforming data sets into smaller, approximate summaries in order to scale Bayesian inference. We examine a related problem in which the parameters of a…
Gradient-based Inference for Networks with Output Constraints
Jay Yoon Lee, Sanket Vaibhav Mehta, Michael Wick +2
Practitioners apply neural networks to increasingly complex problems in natural language processing, such as syntactic parsing and semantic role labeling that have rich output stru…
Filling in the details: Perceiving from low fidelity images
Farahnaz Ahmed Wick, Michael L. Wick, Marc Pomplun
Humans perceive their surroundings in great detail even though most of our visual field is reduced to low-fidelity color-deprived (e.g. dichromatic) input by the retina. In contras…