19 citations · 123 across the 25 of their papers we have counts for
3 papers · 1 filter
Dynamic probabilistic logic models for effective abstractions in RL
Harsha Kokel, Arjun Manoharan, Sriraam Natarajan +2
State abstraction enables sample-efficient learning and better task transfer in complex reinforcement learning environments. Recently, we proposed RePReL (Kokel et al. 2021), a hie…
From Heatmaps to Structural Explanations of Image Classifiers
Li Fuxin, Zhongang Qi, Saeed Khorram +4
This paper summarizes our endeavors in the past few years in terms of explaining image classifiers, with the aim of including negative results and insights we have gained. The pape…
Improving Multilingual Translation by Representation and Gradient Regularization
Yilin Yang, Akiko Eriguchi, Alexandre Muzio +3
Multilingual Neural Machine Translation (NMT) enables one model to serve all translation directions, including ones that are unseen during training, i.e. zero-shot translation. Des…