Peter Yichen Chen

According to our database, Peter Yichen Chen authored at least 19 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Learning Object Properties Using Robot Proprioception via Differentiable Robot-Object Interaction.

Peter Yichen Chen, Chao Liu, Pingchuan Ma, John Eastman, Daniela Rus, Dylan Randle, Yuri Ivanov, Wojciech Matusik

CoRR, 2024

Neural Representation of Shape-Dependent Laplacian Eigenfunctions.

Yue Chang, Otman Benchekroun, Maurizio M. Chiaramonte, Peter Yichen Chen, Eitan Grinspun

CoRR, 2024

Reduced-Order Neural Operators: Learning Lagrangian Dynamics on Highly Sparse Graphs.

Hrishikesh Viswanath, Yue Chang, Julius Berner, Peter Yichen Chen, Aniket Bera

CoRR, 2024

Neural Monte Carlo Fluid Simulation.

Pranav Jain, Ziyin Qu, Peter Yichen Chen, Oded Stein

Proceedings of the ACM SIGGRAPH 2024 Conference Papers, 2024

2023

Model reduction for the material point method via an implicit neural representation of the deformation map.

Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg

J. Comput. Phys., April, 2023

How Can Large Language Models Help Humans in Design and Manufacturing?

Liane Makatura, Michael Foshey, Bohan Wang, Felix Hähnlein, Pingchuan Ma, Bolei Deng, Megan Tjandrasuwita, Andrew Spielberg, Crystal Elaine Owens, Peter Yichen Chen, Allan Zhao, Amy Zhu, Wil J. Norton, Edward Gu, Joshua Jacob, Yifei Li, Adriana Schulz, Wojciech Matusik

CoRR, 2023

Learning Preconditioner for Conjugate Gradient PDE Solvers.

Yichen Li, Peter Yichen Chen, Tao Du, Wojciech Matusik

CoRR, 2023

Neural Stress Fields for Reduced-order Elastoplasticity and Fracture.

Zeshun Zong, Xuan Li, Minchen Li, Maurizio M. Chiaramonte, Wojciech Matusik, Eitan Grinspun, Kevin Carlberg, Chenfanfu Jiang, Peter Yichen Chen

Proceedings of the SIGGRAPH Asia 2023 Conference Papers, 2023

LiCROM: Linear-Subspace Continuous Reduced Order Modeling with Neural Fields.

Yue Chang, Peter Yichen Chen, Zhecheng Wang, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun

Proceedings of the SIGGRAPH Asia 2023 Conference Papers, 2023

Learning Preconditioners for Conjugate Gradient PDE Solvers.

Yichen Li, Peter Yichen Chen, Tao Du, Wojciech Matusik

Proceedings of the International Conference on Machine Learning, 2023

Implicit Neural Spatial Representations for Time-dependent PDEs.

Honglin Chen, Rundi Wu, Eitan Grinspun, Changxi Zheng, Peter Yichen Chen

Proceedings of the International Conference on Machine Learning, 2023

Learning Neural Constitutive Laws from Motion Observations for Generalizable PDE Dynamics.

Pingchuan Ma, Peter Yichen Chen, Bolei Deng, Joshua B. Tenenbaum, Tao Du, Chuang Gan, Wojciech Matusik

Proceedings of the International Conference on Machine Learning, 2023

PAC-NeRF: Physics Augmented Continuum Neural Radiance Fields for Geometry-Agnostic System Identification.

Xuan Li, Yi-Ling Qiao, Peter Yichen Chen, Krishna Murthy Jatavallabhula, Ming C. Lin, Chenfanfu Jiang, Chuang Gan

Proceedings of the Eleventh International Conference on Learning Representations, 2023

CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations.

Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, Yue Chang, G. A. Pershing, Henrique Teles Maia, Maurizio M. Chiaramonte, Kevin T. Carlberg, Eitan Grinspun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022

Multiscaling and Machine Learning Approaches to Physics Simulation

Peter Yichen Chen

PhD thesis, 2022

CROM: Continuous Reduced-Order Modeling of PDEs Using Implicit Neural Representations.

Peter Yichen Chen, Jinxu Xiang, Dong Heon Cho, G. A. Pershing, Henrique Teles Maia, Maurizio M. Chiaramonte, Kevin Carlberg, Eitan Grinspun

CoRR, 2022

2021

Model reduction for the material point method via learning the deformation map and its spatial-temporal gradients.

Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg

CoRR, 2021

Model Reduction for the Material Point Method on Nonlinear Manifolds Using Deep Learning.

Peter Yichen Chen, Maurizio M. Chiaramonte, Eitan Grinspun, Kevin Carlberg

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021

2018

Hybrid grains: adaptive coupling of discrete and continuum simulations of granular media.

Yonghao Yue, Breannan Smith, Peter Yichen Chen, Maytee Chantharayukhonthorn, Ken Kamrin, Eitan Grinspun

ACM Trans. Graph., 2018