Publications

  1. Understanding Dimensional Collapse in Contrastive Self-supervised Learning

    Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian
    International Conference on Learning Representations (ICLR) (2022)

  2. Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations

    Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic
    International Conference on Learning Representations (ICLR) (2022)

  3. Barlow Twins: Self-Supervised Learning via Redundancy Reduction

    Jure Zbontar*, Li Jing*, Ishan Misra, Yann LeCun, Stephane Deny
    International Conference on Machine Learning (ICML) (2021)

  4. Demonstration of Spider‐Eyes‐Like Intelligent Antennas for Dynamically Perceiving Incoming Waves

    Zhedong Wang, Chao Qian, Tong Cai, Longwei Tian, Zhixiang Fan, Jian Liu, Yichen Shen, Li Jing*, Jianming Jin, Er-Ping Li, Bin Zheng, Hongsheng Chen
    Advanced Intelligent Systems (2021)

  5. We Can Explain Your Research in Layman's Terms: Towards Automating Science Journalism at Scale

    Rumen Dangovski, Michelle Shen, Dawson Byrd, Li Jing, Desislava Tsvetkova, Preslav Nakov, Marin Soljacic
    AAAI Conference on Artificial Intelligence (AAAI) (2021)

  6. Implicit Rank-Minimizing Autoencoder

    Li Jing, Jure Zbontar, Yann LeCun
    Conference on Neural Information Processing Systems (NeurIPS) (2020)

  7. Vector-Vector-Matrix Architecture: A Novel Hardware-Aware Framework for Low-Latency Inference in NLP Applications

    Matthew Khoury, Rumen Dangovski, Longwu Ou, Preslav Nakov, Yichen Shen, Li Jing
    Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)

  8. Integration of Neural Network-Based Symbolic Regression in Deep Learning for Scientific Discovery

    Samuel Kim, Peter Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic
    IEEE Transactions on Neural Networks and Learning Systems (TNNLS) (2020)

  9. Predictive and generative machine learning models for photonic crystals

    Thomas Christensen, Charlotte Loh, Stjepan Picek, Domagoj Jakobovic, Li Jing, Sophie Fisher, Vladimir Ceperic, John D. Joannopoulos, Marin Soljacic
    Nanophotonics (2020)

  10. A Recurrent Ising Machine in a Photonic Integrated Circuit

    Mihika Prabhu, Charles Roques-Carmes, Yichen Shen, Nicholas Harris, Li Jing, Jacques Carolan, Ryan Hamerly, Tom Baehr-Jones, Michael Hochberg, Vladimir Ceperic, John Joannopoulos, Dirk Englund, Marin Soljacic
    Optica (2020)

  11. Deep learning enabled self-adaptive invisibility cloak

    Chao Qian, Bin Zheng, Yichen Shen, Li Jing, Erping Li, Lian Shen, Hongsheng Chen
    Nature Photonics (2020)

  12. Heuristic Recurrent Algorithms for Photonic Ising Machines

    Charles Roques-Carmes, Yichen Shen, Cristian Zanoci, Mihika Prabhu, Fadi Atieh, Li Jing, Tena Dubcek, Vladimir Ceperic, John Joannopoulos, Dirk Englund, Marin Soljacic
    Nature Communications (2020)

  13. Rotational Unit of Memory: A Novel Representation Unit for RNNs with Scalable Applications

    Rumen Dangovski*, Li Jing*, Marin Soljačić
    Transactions of the Association for Computational Linguistics (TACL) (2019)

  14. Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks

    Yurui Qu*, Li Jing*, Yichen Shen, Min Qiu, Marin Soljačić
    ACS Photonics (2019)

  15. Gated Orthogonal Recurrent Units: On Learning to Forget

    Li Jing*, Çağlar Gülçehre*, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljačić, Yoshua Bengio
    Neural Computation (2019)

  16. Nanophotonic Particle Simulation and Inverse Design Using Artificial Neural Networks

    John Peurifoy, Yichen Shen, Li Jing, Yi Yang, Fidel Cano-Renteria, Brendan Delacy, John Joannopoulos, Max Tegmark, Marin Soljačić
    Science Advances (2018)

  17. Tunable Efficient Unitary Neural Networks (EUNN) and their application to RNNs

    Li Jing*, Yichen Shen*, Tena Dubček, John Peurifoy, Scott Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic
    International Conference on Machine Learning (ICML) (2017)

  18. Quantum cloning machines and the applications

    Heng Fan, Yi-Nan Wang, Li Jing, Jie-Dong Yue, Han-Duo Shi, Yong-Liang Zhang, Liang-Zhu Mu
    Physics Reports (2014)

  19. Fitting magnetic field gradient with Heisenberg-scaling accuracy

    Yong-Liang Zhang, Huan Wang, Li Jing, Liang-Zhu Mu, Heng Fan
    Scientific Reports (2014)

  20. Quantum network teleportation for quantum information distribution and concentration

    Yong-Liang Zhang, Yi-Nan Wang, Xiang-Ru Xiao, Li Jing, Liang-Zhu Mu, VE Korepin, Heng Fan
    Physical Review A 87 (2013)

  21. Minimal input sets determining phase-covariant and universal quantum cloning

    Li Jing, Yi-Nan Wang, Han-Duo Shi, Liang-Zhu Mu, Heng Fan
    Physical Review A (2012)

  22. General quantum key distribution in higher dimension

    Zhao-Xi Xiong, Han-Duo Shi, Yi-Nan Wang, Li Jing, Jin Lei, Liang-Zhu Mu, Heng Fan
    Physical Review A (2012)

  23. Non-compression of quantum phase information

    Yi-Nan Wang, Han-Duo Shi, Li Jing, Zhao-Xi Xiong, Jin Lei, Liang-Zhu Mu, Heng Fan
    Journal of Physics A: Mathematical and Theoretical (2012)

  24. Unified universal quantum cloning machine and fidelities

    Yi-Nan Wang, Han-Duo Shi, Zhao-Xi Xiong, Li Jing, Xi-Jun Ren, Liang-Zhu Mu, Heng Fan
    Physical Review A (2011)

Pre-prints

Patents