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2020 – today
- 2023
[i15]Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Korthikanti, Weili Nie, De-An Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Ming-Yu Liu, Yuke Zhu, Mohammad Shoeybi, Bryan Catanzaro, Chaowei Xiao, Anima Anandkumar:
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. CoRR abs/2302.04858 (2023)- [i14]Chen Wang, Linxi Fan, Jiankai Sun, Ruohan Zhang, Li Fei-Fei, Danfei Xu, Yuke Zhu, Anima Anandkumar:
MimicPlay: Long-Horizon Imitation Learning by Watching Human Play. CoRR abs/2302.12422 (2023) - [i13]Shikun Liu, Linxi Fan, Edward Johns, Zhiding Yu, Chaowei Xiao, Anima Anandkumar:
Prismer: A Vision-Language Model with An Ensemble of Experts. CoRR abs/2303.02506 (2023) - 2022
- [c11]Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei:
MetaMorph: Learning Universal Controllers with Transformers. ICLR 2022 - [c10]Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar:
MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge. NeurIPS 2022 - [c9]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. NeurIPS 2022 - [i12]Shuang Li, Xavier Puig, Chris Paxton, Yilun Du, Clinton Wang, Linxi Fan, Tao Chen, De-An Huang, Ekin Akyürek, Anima Anandkumar, Jacob Andreas, Igor Mordatch, Antonio Torralba, Yuke Zhu:
Pre-Trained Language Models for Interactive Decision-Making. CoRR abs/2202.01771 (2022) - [i11]Agrim Gupta, Linxi Fan, Surya Ganguli, Li Fei-Fei:
MetaMorph: Learning Universal Controllers with Transformers. CoRR abs/2203.11931 (2022) - [i10]Linxi Fan, Guanzhi Wang, Yunfan Jiang, Ajay Mandlekar, Yuncong Yang, Haoyi Zhu, Andrew Tang, De-An Huang, Yuke Zhu, Anima Anandkumar:
MineDojo: Building Open-Ended Embodied Agents with Internet-Scale Knowledge. CoRR abs/2206.08853 (2022) - [i9]Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, Linxi Fan:
VIMA: General Robot Manipulation with Multimodal Prompts. CoRR abs/2210.03094 (2022) - 2021
- [b1]Linxi Fan:
Training and deploying visual agents at scale. Stanford University, USA, 2021 - [c8]Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Animashree Anandkumar:
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies. ICML 2021: 3088-3099 - [c7]Bokui Shen, Fei Xia, Chengshu Li
, Roberto Martín-Martín, Linxi Fan, Guanzhi Wang, Claudia Pérez-D'Arpino, Shyamal Buch, Sanjana Srivastava, Lyne Tchapmi, Micael Tchapmi, Kent Vainio, Josiah Wong, Li Fei-Fei, Silvio Savarese:
iGibson 1.0: A Simulation Environment for Interactive Tasks in Large Realistic Scenes. IROS 2021: 7520-7527 - [i8]Linxi Fan, Guanzhi Wang, De-An Huang, Zhiding Yu, Li Fei-Fei, Yuke Zhu, Anima Anandkumar:
SECANT: Self-Expert Cloning for Zero-Shot Generalization of Visual Policies. CoRR abs/2106.09678 (2021) - 2020
- [c6]Linxi Fan, Shyamal Buch, Guanzhi Wang, Ryan Cao, Yuke Zhu, Juan Carlos Niebles, Li Fei-Fei:
RubiksNet: Learnable 3D-Shift for Efficient Video Action Recognition. ECCV (19) 2020: 505-521 - [i7]Bokui Shen, Fei Xia, Chengshu Li, Roberto Martín-Martín, Linxi Fan, Guanzhi Wang, Shyamal Buch, Claudia D'Arpino, Sanjana Srivastava, Lyne P. Tchapmi, Micael E. Tchapmi, Kent Vainio, Li Fei-Fei, Silvio Savarese:
iGibson, a Simulation Environment for Interactive Tasks in Large Realistic Scenes. CoRR abs/2012.02924 (2020)
2010 – 2019
- 2019
- [j2]Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel Hsu, Brian Kingsbury, Michael Picheny, Fei Sha:
Kernel Approximation Methods for Speech Recognition. J. Mach. Learn. Res. 20: 59:1-59:36 (2019) - [i6]Linxi Fan, Yuke Zhu, Jiren Zhu, Zihua Liu, Orien Zeng, Anchit Gupta, Joan Creus-Costa, Silvio Savarese, Li Fei-Fei:
SURREAL-System: Fully-Integrated Stack for Distributed Deep Reinforcement Learning. CoRR abs/1909.12989 (2019) - 2018
- [c5]Linxi Fan, Yuke Zhu, Jiren Zhu, Zihua Liu, Orien Zeng, Anchit Gupta, Joan Creus-Costa, Silvio Savarese, Li Fei-Fei:
SURREAL: Open-Source Reinforcement Learning Framework and Robot Manipulation Benchmark. CoRL 2018: 767-782 - 2017
- [j1]Miguel Francisco M. Remolona, Matthew F. Conway, Sriram Balasubramanian, Linxi Fan, Ziyan Feng, Tianhao Gu, Hyungtae Kim, Prasad M. Nirantar, Sarah Panda, Nithin R. Ranabothu, Neha Rastogi, Venkat Venkatasubramanian:
Hybrid ontology-learning materials engineering system for pharmaceutical products: Multi-label entity recognition and concept detection. Comput. Chem. Eng. 107: 49-60 (2017) - [c4]Tianlin Shi, Andrej Karpathy, Linxi Fan, Jonathan Hernandez, Percy Liang:
World of Bits: An Open-Domain Platform for Web-Based Agents. ICML 2017: 3135-3144 - [i5]Avner May, Alireza Bagheri Garakani, Zhiyun Lu, Dong Guo, Kuan Liu, Aurélien Bellet, Linxi Fan, Michael Collins, Daniel J. Hsu, Brian Kingsbury, Michael Picheny, Fei Sha:
Kernel Approximation Methods for Speech Recognition. CoRR abs/1701.03577 (2017) - 2016
- [c3]Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
A comparison between deep neural nets and kernel acoustic models for speech recognition. ICASSP 2016: 5070-5074 - [c2]Dario Amodei, Sundaram Ananthanarayanan, Rishita Anubhai, Jingliang Bai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Awni Y. Hannun, Billy Jun, Tony Han, Patrick LeGresley, Xiangang Li, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Sheng Qian, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Chong Wang, Yi Wang, Zhiqian Wang, Bo Xiao, Yan Xie, Dani Yogatama, Jun Zhan, Zhenyao Zhu:
Deep Speech 2 : End-to-End Speech Recognition in English and Mandarin. ICML 2016: 173-182 - [c1]Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio:
Deconstructing the Ladder Network Architecture. ICML 2016: 2368-2376 - [i4]Zhiyun Lu, Dong Guo, Alireza Bagheri Garakani, Kuan Liu, Avner May, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
A Comparison between Deep Neural Nets and Kernel Acoustic Models for Speech Recognition. CoRR abs/1603.05800 (2016) - 2015
- [i3]Mohammad Pezeshki, Linxi Fan, Philemon Brakel, Aaron C. Courville, Yoshua Bengio:
Deconstructing the Ladder Network Architecture. CoRR abs/1511.06430 (2015) - [i2]Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse H. Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Y. Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Y. Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu:
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin. CoRR abs/1512.02595 (2015) - 2014
- [i1]Zhiyun Lu, Avner May, Kuan Liu, Alireza Bagheri Garakani, Dong Guo, Aurélien Bellet, Linxi Fan, Michael Collins, Brian Kingsbury, Michael Picheny, Fei Sha:
How to Scale Up Kernel Methods to Be As Good As Deep Neural Nets. CoRR abs/1411.4000 (2014)
Coauthor Index
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last updated on 2023-05-12 21:00 CEST by the dblp team
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