Li Jing

According to our database, Li Jing authored at least 28 papers between 2016 and 2024.

Collaborative distances:

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

2024

Data-Informed Global Sparseness in Attention Mechanisms for Deep Neural Networks.

Ileana Rugina, Rumen Dangovski, Li Jing, Preslav Nakov, Marin Soljacic

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

2023

VoLTA: Vision-Language Transformer with Weakly-Supervised Local-Feature Alignment.

Shraman Pramanick, Li Jing, Sayan Nag, Jiachen Zhu, Hardik Shah, Yann LeCun, Rama Chellappa

Trans. Mach. Learn. Res., 2023

Contextualizing Enhances Gradient Based Meta Learning for Few Shot Image Classification.

Evan Vogelbaum, Rumen Dangovski, Li Jing, Marin Soljacic

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

Manifold Transfer Networks for Lens Distortion Rectification.

Li Jing, Lay Jain, Rumen Dangovski, Marin Soljacic

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

Asymmetric Grouped Convolutions for Logarithmic Scale Efficient Convolutional Neural Networks.

Li Jing, Rumen Dangovski, Marin Soljacic

Proceedings of the IEEE High Performance Extreme Computing Conference, 2023

2022

Masked Siamese ConvNets.

Li Jing, Jiachen Zhu, Yann LeCun

CoRR, 2022

Positive Unlabeled Contrastive Learning.

Anish Acharya, Sujay Sanghavi, Li Jing, Bhargav Bhushanam, Dhruv Choudhary, Michael G. Rabbat, Inderjit S. Dhillon

CoRR, 2022

Topogivity: A Machine-Learned Chemical Rule for Discovering Topological Materials.

Andrew Ma, Yang Zhang, Thomas Christensen, Hoi Chun Po, Li Jing, Liang Fu, Marin Soljacic

CoRR, 2022

Understanding Dimensional Collapse in Contrastive Self-supervised Learning.

Li Jing, Pascal Vincent, Yann LeCun, Yuandong Tian

Proceedings of the Tenth International Conference on Learning Representations, 2022

Equivariant Self-Supervised Learning: Encouraging Equivariance in Representations.

Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic

Proceedings of the Tenth International Conference on Learning Representations, 2022

2021

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

Samuel Kim, Peter Y. Lu, Srijon Mukherjee, Michael Gilbert, Li Jing, Vladimir Ceperic, Marin Soljacic

IEEE Trans. Neural Networks Learn. Syst., 2021

Equivariant Contrastive Learning.

Rumen Dangovski, Li Jing, Charlotte Loh, Seungwook Han, Akash Srivastava, Brian Cheung, Pulkit Agrawal, Marin Soljacic

CoRR, 2021

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

Adv. Intell. Syst., 2021

Barlow Twins: Self-Supervised Learning via Redundancy Reduction.

Jure Zbontar, Li Jing, Ishan Misra, Yann LeCun, Stéphane Deny

Proceedings of the 38th International Conference on Machine Learning, 2021

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

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Contextualizing Enhances Gradient Based Meta Learning.

Evan Vogelbaum, Rumen Dangovski, Li Jing, Marin Soljacic

CoRR, 2020

Implicit Rank-Minimizing Autoencoder.

Li Jing, Jure Zbontar, Yann LeCun

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

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

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

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

Rumen Dangovski, Li Jing, Preslav Nakov, Mico Tatalovic, Marin Soljacic

Trans. Assoc. Comput. Linguistics, 2019

Gated Orthogonal Recurrent Units: On Learning to Forget.

Li Jing, Çaglar Gülçehre, John Peurifoy, Yichen Shen, Max Tegmark, Marin Soljacic, Yoshua Bengio

Neural Comput., 2019

2018

WaveletNet: Logarithmic Scale Efficient Convolutional Neural Networks for Edge Devices.

Li Jing, Rumen Dangovski, Marin Soljacic

CoRR, 2018

Photonic Recurrent Ising Sampler.

Charles Roques-Carmes, Yichen Shen, Cristian Zanoci, Mihika Prabhu, Fadi Atieh, Li Jing, Tena Dubcek, Vladimir Ceperic, John D. Joannopoulos, Dirk R. Englund, Marin Soljacic

CoRR, 2018

Migrating Knowledge between Physical Scenarios based on Artificial Neural Networks.

Yurui Qu, Li Jing, Yichen Shen, Min Qiu, Marin Soljacic

CoRR, 2018

Statistical Computing in Photonic Integrated Circuits.

Yichen Shen, Huaiyu Meng, Li Jing, Bobby Lu

Proceedings of the Photonics in Switching and Computing, 2018

Rotational Unit of Memory.

Rumen Dangovski, Li Jing, Marin Soljacic

Proceedings of the 6th International Conference on Learning Representations, 2018

Improving the Performance of Unitary Recurrent Neural Networks and Their Application in Real-life Tasks.

Ivan Ivanov, Li Jing, Rumen Dangovski

Proceedings of the 19th International Conference on Computer Systems and Technologies, 2018

2017

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

Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Yann LeCun, Max Tegmark, Marin Soljacic

Proceedings of the 34th International Conference on Machine Learning, 2017

2016

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

Li Jing, Yichen Shen, Tena Dubcek, John Peurifoy, Scott A. Skirlo, Max Tegmark, Marin Soljacic

CoRR, 2016