Yen-Yu Chang

Learning Object-Centric Neural Scattering Functions for Free-viewpoint Relighting and Scene Composition

Mar 10, 2023
Hong-Xing Yu, Michelle Guo, Alireza Fathi, Yen-Yu Chang, Eric Ryan Chan, Ruohan Gao, Thomas Funkhouser, Jiajun Wu

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* Journal extension of arXiv:2012.08503. The first two authors contributed equally to this work

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Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows

Feb 27, 2023
Anna Willmann, Jurjen Couperus Cabadağ, Yen-Yu Chang, Richard Pausch, Amin Ghaith, Alexander Debus, Arie Irman, Michael Bussmann, Ulrich Schramm, Nico Hoffmann

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* Machine Learning and the Physical Sciences 2022 workshop, NeurIPS
* 7 pages, 5 figures

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ObjectFolder 2.0: A Multisensory Object Dataset for Sim2Real Transfer

Apr 05, 2022
Ruohan Gao, Zilin Si, Yen-Yu Chang, Samuel Clarke, Jeannette Bohg, Li Fei-Fei, Wenzhen Yuan, Jiajun Wu

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* In CVPR 2022. Gao, Si, and Chang contributed equally to this work. Project page: https://ai.stanford.edu/~rhgao/objectfolder2.0/

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ObjectFolder: A Dataset of Objects with Implicit Visual, Auditory, and Tactile Representations

Sep 18, 2021
Ruohan Gao, Yen-Yu Chang, Shivani Mall, Li Fei-Fei, Jiajun Wu

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* In CoRL 2021. Chang and Mall contributed equally to this work. Project page: https://ai.stanford.edu/~rhgao/objectfolder/

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Data-Driven Shadowgraph Simulation of a 3D Object

Jun 01, 2021
Anna Willmann, Patrick Stiller, Alexander Debus, Arie Irman, Richard Pausch, Yen-Yu Chang, Michael Bussmann, Nico Hoffmann

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* 9 pages, 9 figures. Published as a workshop paper at ICLR 2021 SimDL Workshop

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Inductive Representation Learning in Temporal Networks via Causal Anonymous Walks

Jan 15, 2021
Yanbang Wang, Yen-Yu Chang, Yunyu Liu, Jure Leskovec, Pan Li

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* Accepted to ICLR 2021

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F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams

Nov 09, 2020
Yen-Yu Chang, Pan Li, Rok Sosic, M. H. Afifi, Marco Schweighauser, Jure Leskovec

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* WSDM 2021

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A Regulation Enforcement Solution for Multi-agent Reinforcement Learning

Jan 29, 2019
Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin

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* Accepted at AAMAS 2019 for extended abstract

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ANS: Adaptive Network Scaling for Deep Rectifier Reinforcement Learning Models

Oct 31, 2018
Yueh-Hua Wu, Fan-Yun Sun, Yen-Yu Chang, Shou-De Lin

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A Memory-Network Based Solution for Multivariate Time-Series Forecasting

Sep 06, 2018
Yen-Yu Chang, Fan-Yun Sun, Yueh-Hua Wu, Shou-De Lin

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* 8 pages, 4 figures, submitted to AAAI 2019. arXiv admin note: text overlap with arXiv:1703.07015 by other authors

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