163 citations · 589 across the 42 of their papers we have counts for
6 papers · 1 filter
Identifying Reasoning Flaws in Planning-Based RL Using Tree Explanations
Kin-Ho Lam, Zhengxian Lin, Jed Irvine +5
Enabling humans to identify potential flaws in an agent's decision making is an important Explainable AI application. We consider identifying such flaws in a planning-based deep re…
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…
Out-of-Distribution Dynamics Detection: RL-Relevant Benchmarks and Results
Mohamad H Danesh, Alan Fern
We study the problem of out-of-distribution dynamics (OODD) detection, which involves detecting when the dynamics of a temporal process change compared to the training-distribution…
Piecewise-constant Neural ODEs
Sam Greydanus, Stefan Lee, Alan Fern
Neural networks are a popular tool for modeling sequential data but they generally do not treat time as a continuous variable. Neural ODEs represent an important exception: they pa…
Blind Bipedal Stair Traversal via Sim-to-Real Reinforcement Learning
Jonah Siekmann, Kevin Green, John Warila +2
Accurate and precise terrain estimation is a difficult problem for robot locomotion in real-world environments. Thus, it is useful to have systems that do not depend on accurate es…
Deep Convolution for Irregularly Sampled Temporal Point Clouds
Erich Merrill, Stefan Lee, Li Fuxin +2
We consider the problem of modeling the dynamics of continuous spatial-temporal processes represented by irregular samples through both space and time. Such processes occur in sens…