828 citations · 5.6k across the 171 of their papers we have counts for
17 papers · 1 filter
Unsupervised Hierarchy Matching with Optimal Transport over Hyperbolic Spaces
David Alvarez-Melis, Youssef Mroueh, Tommi S. Jaakkola
This paper focuses on the problem of unsupervised alignment of hierarchical data such as ontologies or lexical databases. This is a problem that appears across areas, from natural…
A Game Theoretic Approach to Class-wise Selective Rationalization
Shiyu Chang, Yang Zhang, Mo Yu +1
Selection of input features such as relevant pieces of text has become a common technique of highlighting how complex neural predictors operate. The selection can be optimized post…
Learning to Make Generalizable and Diverse Predictions for Retrosynthesis
Benson Chen, Tianxiao Shen, Tommi S. Jaakkola +1
We propose a new model for making generalizable and diverse retrosynthetic reaction predictions. Given a target compound, the task is to predict the likely chemical reactants to pr…
Rethinking Cooperative Rationalization: Introspective Extraction and Complement Control
Mo Yu, Shiyu Chang, Yang Zhang +1
Selective rationalization has become a common mechanism to ensure that predictive models reveal how they use any available features. The selection may be soft or hard, and identifi…
Oblique Decision Trees from Derivatives of ReLU Networks
Guang-He Lee, Tommi S. Jaakkola
We show how neural models can be used to realize piece-wise constant functions such as decision trees. The proposed architecture, which we call locally constant networks, builds on…
Towards Robust, Locally Linear Deep Networks
Guang-He Lee, David Alvarez-Melis, Tommi S. Jaakkola
Deep networks realize complex mappings that are often understood by their locally linear behavior at or around points of interest. For example, we use the derivative of the mapping…