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Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding

Published in NeurIPS, 2023

We designed the Laplacian Canonization algorithm to address the sign and basis ambiguities of Laplacian eigenvectors.

Recommended citation: Jiangyan Ma, Yifei Wang, Yisen Wang (2023). Laplacian Canonization: A Minimalist Approach to Sign and Basis Invariant Spectral Embedding. In Thirty-seventh Conference on Neural Information Processing Systems. https://openreview.net/forum?id=1mAYtdoYw6

Baking Symmetry into GFlowNets

Published in NeurIPS-AI4Science, 2023

We proposed to incorporate state and action symmetries into GFlowNets.

Recommended citation: Jiangyan Ma, Emmanuel Bengio, Yoshua Bengio, Dinghuai Zhang (2023). Baking Symmetry into GFlowNets. In NeurIPS 2023 AI for Science: from Theory to Practice. https://openreview.net/forum?id=CZGHAeeBk3

A Canonization Perspective on Invariant and Equivariant Learning

Published in NeurIPS, 2024

We analysed the efficiency and expressiveness of invariant and equivariant networks from a canonization perspective.

Recommended citation: George Ma, Yifei Wang, Derek Lim, Stefanie Jegelka, Yisen Wang (2024). A Canonization Perspective on Invariant and Equivariant Learning. In Thirty-eighth Conference on Neural Information Processing Systems. https://arxiv.org/abs/2405.18378

Talk 1 on Relevant Topic in Your Field

Published: March 01, 2012

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Tutorial 1 on Relevant Topic in Your Field

Published: March 01, 2013

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Talk 2 on Relevant Topic in Your Field

Published: February 01, 2014

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Conference Proceeding talk 3 on Relevant Topic in Your Field

Published: March 01, 2014

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Teaching experience 1

Undergraduate course, University 1, Department, 2014

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Teaching experience 2

Workshop, University 1, Department, 2015

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