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ViRel: Unsupervised Visual Relations Discovery with Graph-level Analogy


Jul 04, 2022
Daniel Zeng, Tailin Wu, Jure Leskovec

* ICML 2022 Beyond Bayes: Paths Towards Universal Reasoning Systems Workshop; 17 pages, 10 figures 

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ZeroC: A Neuro-Symbolic Model for Zero-shot Concept Recognition and Acquisition at Inference Time


Jul 03, 2022
Tailin Wu, Megan Tjandrasuwita, Zhengxuan Wu, Xuelin Yang, Kevin Liu, Rok Sosič, Jure Leskovec

* 25 pages, 9 figures 

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Learning to Accelerate Partial Differential Equations via Latent Global Evolution


Jun 15, 2022
Tailin Wu, Takashi Maruyama, Jure Leskovec

* 25 pages, 13 figures 

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Learning Large-scale Subsurface Simulations with a Hybrid Graph Network Simulator


Jun 15, 2022
Tailin Wu, Qinchen Wang, Yinan Zhang, Rex Ying, Kaidi Cao, Rok Sosič, Ridwan Jalali, Hassan Hamam, Marko Maucec, Jure Leskovec

* SIGKDD 2022; 11 pages, 6 figures 

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Graph Information Bottleneck


Oct 24, 2020
Tailin Wu, Hongyu Ren, Pan Li, Jure Leskovec

* 20 pages, 3 figures, NeurIPS 2020 

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AI Feynman 2.0: Pareto-optimal symbolic regression exploiting graph modularity


Jun 18, 2020
Silviu-Marian Udrescu, Andrew Tan, Jiahai Feng, Orisvaldo Neto, Tailin Wu, Max Tegmark

* 16 pages, 6 figs 

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Intelligence, physics and information -- the tradeoff between accuracy and simplicity in machine learning


Jan 20, 2020
Tailin Wu

* PhD Thesis, 352 pages. Reference improved 

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Discovering Nonlinear Relations with Minimum Predictive Information Regularization


Jan 07, 2020
Tailin Wu, Thomas Breuel, Michael Skuhersky, Jan Kautz

* 26 pages, 11 figures; ICML'19 Time Series Workshop 

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