841 citations · 1.8k across the 37 of their papers we have counts for
6 papers · 1 filter
Barking up the right tree: an approach to search over molecule synthesis DAGs
John Bradshaw, Brooks Paige, Matt J. Kusner +2
When designing new molecules with particular properties, it is not only important what to make but crucially how to make it. These instructions form a synthesis directed acyclic gr…
Learning Binary Decision Trees by Argmin Differentiation
Valentina Zantedeschi, Matt J. Kusner, Vlad Niculae
We address the problem of learning binary decision trees that partition data for some downstream task. We propose to learn discrete parameters (i.e., for tree traversals and node p…
Unsupervised Point Cloud Pre-Training via Occlusion Completion
Hanchen Wang, Qi Liu, Xiangyu Yue +2
We describe a simple pre-training approach for point clouds. It works in three steps: 1. Mask all points occluded in a camera view; 2. Learn an encoder-decoder model to reconstruct…
A Class of Algorithms for General Instrumental Variable Models
Niki Kilbertus, Matt J. Kusner, Ricardo Silva
Causal treatment effect estimation is a key problem that arises in a variety of real-world settings, from personalized medicine to governmental policy making. There has been a flur…
A Survey on Contextual Embeddings
Qi Liu, Matt J. Kusner, Phil Blunsom
Contextual embeddings, such as ELMo and BERT, move beyond global word representations like Word2Vec and achieve ground-breaking performance on a wide range of natural language proc…
Differentiable Causal Backdoor Discovery
Limor Gultchin, Matt J. Kusner, Varun Kanade +1
Discovering the causal effect of a decision is critical to nearly all forms of decision-making. In particular, it is a key quantity in drug development, in crafting government poli…