37 citations · 39 across the 2 of their papers we have counts for
3 papers
cs.LG2020★ 2 cited
Provably Efficient Third-Person Imitation from Offline Observation
Aaron Zweig, Joan Bruna
Domain adaptation in imitation learning represents an essential step towards improving generalizability. However, even in the restricted setting of third-person imitation where tra…
stat.ML2019★ 37 cited
Stochastic Optimization of Sorting Networks via Continuous Relaxations
Aditya Grover, Eric Wang, Aaron Zweig +1
Sorting input objects is an important step in many machine learning pipelines. However, the sorting operator is non-differentiable with respect to its inputs, which prohibits end-t…
stat.ML2018
Graphite: Iterative Generative Modeling of Graphs
Aditya Grover, Aaron Zweig, Stefano Ermon
Graphs are a fundamental abstraction for modeling relational data. However, graphs are discrete and combinatorial in nature, and learning representations suitable for machine learn…