2 code implementations • 13 Feb 2024 • Emily Jin, Michael Bronstein, Ismail Ilkan Ceylan, Matthias Lanzinger
A large body of work has investigated the properties of graph neural networks and identified several limitations, particularly pertaining to their expressive power.
1 code implementation • 3 Oct 2023 • Emily Jin, Jiaheng Hu, Zhuoyi Huang, Ruohan Zhang, Jiajun Wu, Li Fei-Fei, Roberto Martín-Martín
We present Mini-BEHAVIOR, a novel benchmark for embodied AI that challenges agents to use reasoning and decision-making skills to solve complex activities that resemble everyday human challenges.
no code implementations • 27 May 2023 • Andrey Kurenkov, Michael Lingelbach, Tanmay Agarwal, Emily Jin, Chengshu Li, Ruohan Zhang, Li Fei-Fei, Jiajun Wu, Silvio Savarese, Roberto Martín-Martín
We evaluate our method in the Dynamic House Simulator, a new benchmark that creates diverse dynamic graphs following the semantic patterns typically seen at homes, and show that NEP can be trained to predict the locations of objects in a variety of environments with diverse object movement dynamics, outperforming baselines both in terms of new scene adaptability and overall accuracy.