Timezone: »
Complex systems are often decomposed into modular subsystems for engineering tractability. Although various equation based white-box modeling techniques make use of such structure, learning based methods have yet to incorporate these ideas broadly. We present a modular simulation framework for modeling homogeneous multibody dynamical systems, which combines ideas from graph neural networks and neural differential equations. We learn to model the individual dynamical subsystem as a neural ODE module. Full simulation of the composite system is orchestrated via spatio-temporal message passing between these modules. An arbitrary number of modules can be combined to simulate systems of a wide variety of coupling topologies. We evaluate our framework on a variety of systems and show that message passing allows coordination between multiple modules over time for accurate predictions and in certain cases, enables zero-shot generalization to new system configurations. Furthermore, we show that our models can be transferred to new system configurations with lower data requirement and training effort, compared to those trained from scratch.
Author Information
Jayesh Gupta (Microsoft)
Sai Vemprala (Microsoft)
Ashish Kapoor (Microsoft)
More from the Same Authors
-
2020 : Paper 64: Modeling Affect-based Intrinsic Rewards for Exploration and Learning »
Daniel McDuff · Ashish Kapoor -
2021 Spotlight: Representation Learning for Event-based Visuomotor Policies »
Sai Vemprala · Sami Mian · Ashish Kapoor -
2022 : PACT: Perception-Action Causal Transformer for Autoregressive Robotics Pretraining »
Rogerio Bonatti · Sai Vemprala · shuang ma · Felipe Vieira Frujeri · Shuhang Chen · Ashish Kapoor -
2022 : SMART: Self-supervised Multi-task pretrAining with contRol Transformers »
Yanchao Sun · shuang ma · Ratnesh Madaan · Rogerio Bonatti · Furong Huang · Ashish Kapoor -
2022 : LATTE: LAnguage Trajectory TransformEr »
A Bucker · Luis Figueredo · Sami Haddadin · Ashish Kapoor · shuang ma · Sai Vemprala · Rogerio Bonatti -
2022 Poster: 3DB: A Framework for Debugging Computer Vision Models »
Guillaume Leclerc · Hadi Salman · Andrew Ilyas · Sai Vemprala · Logan Engstrom · Vibhav Vineet · Kai Xiao · Pengchuan Zhang · Shibani Santurkar · Greg Yang · Ashish Kapoor · Aleksander Madry -
2021 Poster: Representation Learning for Event-based Visuomotor Policies »
Sai Vemprala · Sami Mian · Ashish Kapoor -
2021 Poster: Unadversarial Examples: Designing Objects for Robust Vision »
Hadi Salman · Andrew Ilyas · Logan Engstrom · Sai Vemprala · Aleksander Madry · Ashish Kapoor -
2020 Poster: Do Adversarially Robust ImageNet Models Transfer Better? »
Hadi Salman · Andrew Ilyas · Logan Engstrom · Ashish Kapoor · Aleksander Madry -
2020 Oral: Do Adversarially Robust ImageNet Models Transfer Better? »
Hadi Salman · Andrew Ilyas · Logan Engstrom · Ashish Kapoor · Aleksander Madry -
2020 Poster: Denoised Smoothing: A Provable Defense for Pretrained Classifiers »
Hadi Salman · Mingjie Sun · Greg Yang · Ashish Kapoor · J. Zico Kolter -
2020 Poster: Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates »
Wenhao Luo · Wen Sun · Ashish Kapoor -
2020 Spotlight: Multi-Robot Collision Avoidance under Uncertainty with Probabilistic Safety Barrier Certificates »
Wenhao Luo · Wen Sun · Ashish Kapoor -
2019 : The Game of Drones Competition »
Charbel Toumieh · Sai Vemprala · Sangyun Shin · Rahul Kumar · Andrey Ivanov · Hyunchul Shim · Jose Martinez-Carranza · Nicholas Gyde · Ashish Kapoor · Keiko Nagami · Tim Taubner · Ratnesh Madaan · Antony Gillette · Paul Stubbs -
2019 : Lunch + Poster Session »
Frederik Gerzer · Bill Yang Cai · Pieter-Jan Hoedt · Kelly Kochanski · Soo Kyung Kim · Yunsung Lee · Sunghyun Park · Sharon Zhou · Martin Gauch · Jonathan Wilson · Joyjit Chatterjee · Shamindra Shrotriya · Dimitri Papadimitriou · Christian Schön · Valentina Zantedeschi · Gabriella Baasch · Willem Waegeman · Gautier Cosne · Dara Farrell · Brendan Lucier · Letif Mones · Caleb Robinson · Tafara Chitsiga · Victor Kristof · Hari Prasanna Das · Yimeng Min · Alexandra Puchko · Alexandra Luccioni · Kyle Story · Jason Hickey · Yue Hu · Björn Lütjens · Zhecheng Wang · Renzhi Jing · Genevieve Flaspohler · Jingfan Wang · Saumya Sinha · Qinghu Tang · Armi Tiihonen · Ruben Glatt · Muge Komurcu · Jan Drgona · Juan Gomez-Romero · Ashish Kapoor · Dylan J Fitzpatrick · Alireza Rezvanifar · Adrian Albert · Olya (Olga) Irzak · Kara Lamb · Ankur Mahesh · Kiwan Maeng · Frederik Kratzert · Sorelle Friedler · Niccolo Dalmasso · Alex Robson · Lindiwe Malobola · Lucas Maystre · Yu-wen Lin · Surya Karthik Mukkavili · Brian Hutchinson · Alexandre Lacoste · Yanbing Wang · Zhengcheng Wang · Yinda Zhang · Victoria Preston · Jacob Pettit · Draguna Vrabie · Miguel Molina-Solana · Tonio Buonassisi · Andrew Annex · Tunai P Marques · Catalin Voss · Johannes Rausch · Max Evans -
2019 Poster: Characterizing Bias in Classifiers using Generative Models »
Daniel McDuff · Shuang Ma · Yale Song · Ashish Kapoor -
2019 Poster: Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting »
Aditya Grover · Jiaming Song · Ashish Kapoor · Kenneth Tran · Alekh Agarwal · Eric Horvitz · Stefano Ermon -
2016 Poster: Quantum Perceptron Models »
Ashish Kapoor · Nathan Wiebe · Krysta Svore -
2015 : Machine Learning as Rotations (Quantum Deep Learning) »
Ashish Kapoor -
2012 Poster: Multilabel Classification using Bayesian Compressed Sensing »
Ashish Kapoor · Raajay Viswanathan · Prateek Jain -
2009 Workshop: Analysis and Design of Algorithms for Interactive Machine Learning »
Sumit Basu · Ashish Kapoor -
2009 Poster: Breaking Boundaries Between Induction Time and Diagnosis Time Active Information Acquisition »
Ashish Kapoor · Eric Horvitz