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Publication search results
found 62 matches
- 2024
- Ruiquan Huang, Yingbin Liang, Jing Yang:
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations. ICLR 2024 - Oli Danyi Liu, Hao Tang, Naomi Feldman, Sharon Goldwater:
A predictive learning model can simulate temporal dynamics and context effects found in neural representations of continuous speech. CoRR abs/2405.08237 (2024) - 2023
- Vladimir Araujo
, Marie-Francine Moens, Alvaro Soto:
Learning Sentence-Level Representations with Predictive Coding. Mach. Learn. Knowl. Extr. 5(1): 59-77 (2023) - Zihao Wang
, Chunxu Wu, Yifei Yang, Zhen Li:
Learning Transformation-Predictive Representations for Detection and Description of Local Features. CVPR 2023: 11464-11473 - David Medina-Ortiz, Pedro Salinas, Gabriel Cabas-Moras, Fabio Durán-Verdugo, Alvaro Olivera-Nappa
, Roberto Uribe Paredes:
Exploring Machine Learning Algorithms and Numerical Representations Strategies to Develop Sequence-Based Predictive Models for Protein Networks. ICCSA (1) 2023: 231-244 - Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee:
PAC Reinforcement Learning for Predictive State Representations. ICLR 2023 - Tianjun Zhang, Tongzheng Ren, Chenjun Xiao, Wenli Xiao, Joseph E. Gonzalez, Dale Schuurmans, Bo Dai:
Energy-based Predictive Representations for Partially Observed Reinforcement Learning. UAI 2023: 2477-2487 - Xia Xu, Jochen Triesch:
CIPER: Combining Invariant and Equivariant Representations Using Contrastive and Predictive Learning. CoRR abs/2302.02330 (2023) - Ruiquan Huang, Yingbin Liang, Jing Yang:
Provably Efficient UCB-type Algorithms For Learning Predictive State Representations. CoRR abs/2307.00405 (2023) - Julia Huiming Wang, Dexter Tsin, Tatiana Engel:
Predictive variational autoencoder for learning robust representations of time-series data. CoRR abs/2312.06932 (2023) - 2022
- Avi Ziskind
, Sujeong Kim, Giedrius T. Burachas:
Learning Invariant World State Representations with Predictive Coding. CoRR abs/2207.02972 (2022) - Wenhao Zhan, Masatoshi Uehara, Wen Sun, Jason D. Lee:
PAC Reinforcement Learning for Predictive State Representations. CoRR abs/2207.05738 (2022) - 2021
- Michael Geden, Andrew Emerson
, Dan Carpenter, Jonathan P. Rowe, Roger Azevedo, James C. Lester:
Predictive Student Modeling in Game-Based Learning Environments with Word Embedding Representations of Reflection. Int. J. Artif. Intell. Educ. 31(1): 1-23 (2021) - Janek Ebbers, Michael Kuhlmann, Tobias Cord-Landwehr, Reinhold Haeb-Umbach:
Contrastive Predictive Coding Supported Factorized Variational Autoencoder For Unsupervised Learning Of Disentangled Speech Representations. ICASSP 2021: 3860-3864 - Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Self-Predictive Representations. ICLR 2021 - Alexander H. Liu, Yu-An Chung, James R. Glass:
Non-Autoregressive Predictive Coding for Learning Speech Representations from Local Dependencies. Interspeech 2021: 3730-3734 - Sathyanarayanan N. Aakur, Sudeep Sarkar:
Learning Actor-centered Representations for Action Localization in Streaming Videos using Predictive Learning. CoRR abs/2104.14131 (2021) - 2020
- Lucas Lehnert
, Michael L. Littman, Michael J. Frank
:
Reward-predictive representations generalize across tasks in reinforcement learning. PLoS Comput. Biol. 16(10) (2020) - Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto:
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation. CoRL 2020: 564-574 - Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar:
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning. ICML 2020: 3875-3886 - Wilson Yan, Ashwin Vangipuram, Pieter Abbeel, Lerrel Pinto:
Learning Predictive Representations for Deformable Objects Using Contrastive Estimation. CoRR abs/2003.05436 (2020) - Zhaohan Daniel Guo, Bernardo Ávila Pires, Bilal Piot, Jean-Bastien Grill, Florent Altché, Rémi Munos, Mohammad Gheshlaghi Azar:
Bootstrap Latent-Predictive Representations for Multitask Reinforcement Learning. CoRR abs/2004.14646 (2020) - Janek Ebbers, Michael Kuhlmann, Reinhold Haeb-Umbach:
Adversarial Contrastive Predictive Coding for Unsupervised Learning of Disentangled Representations. CoRR abs/2005.12963 (2020) - Daniel Graves, Nhat M. Nguyen, Kimia Hassanzadeh, Jun Jin:
Learning predictive representations in autonomous driving to improve deep reinforcement learning. CoRR abs/2006.15110 (2020) - Max Schwarzer, Ankesh Anand, Rishab Goel, R. Devon Hjelm, Aaron C. Courville, Philip Bachman:
Data-Efficient Reinforcement Learning with Momentum Predictive Representations. CoRR abs/2007.05929 (2020) - Alexander H. Liu, Yu-An Chung, James R. Glass:
Non-Autoregressive Predictive Coding for Learning Speech Representations from Local Dependencies. CoRR abs/2011.00406 (2020) - 2019
- Haohan Wang, Songwei Ge, Zachary C. Lipton, Eric P. Xing:
Learning Robust Global Representations by Penalizing Local Predictive Power. NeurIPS 2019: 10506-10518 - Haohan Wang, Songwei Ge, Eric P. Xing, Zachary C. Lipton:
Learning Robust Global Representations by Penalizing Local Predictive Power. CoRR abs/1905.13549 (2019) - Oliver Struckmeier, Kshitij Tiwari, Shirin Dora, Martin J. Pearson, Sander M. Bohté, Cyriel M. A. Pennartz, Ville Kyrki:
MuPNet: Multi-modal Predictive Coding Network for Place Recognition by Unsupervised Learning of Joint Visuo-Tactile Latent Representations. CoRR abs/1909.07201 (2019) - 2018
- Chunqing Huang, Yisheng An, Sun Zhou, Zhezheng Hong, Yunlong Liu
:
Basis selection in spectral learning of predictive state representations. Neurocomputing 310: 183-189 (2018)
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