Paper

  • Learning to Modulate pre-trained Models in RL

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Modulate pre-trained Models in RL

    Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter p38231-38265 from Advances in Neural Information Processing Systems 36
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  • Learning to Navigate Wikipedia by Taking Random Walks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Navigate Wikipedia by Taking Random Walks

    Manzil Zaheer, Kenneth Marino, Will Grathwohl, John Schultz, Wendy Shang, Sheila Babayan, Arun Ahuja, Ishita Dasgupta, Christine Kaeser-Chen, Rob Fergus p1529-1541 from Advances in Neural Information Processing Systems 35
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  • Learning to Parameterize Visual Attributes for Open-set Fine-grained Retrieval

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Parameterize Visual Attributes for Open-set Fine-grained Retrieval

    Shijie Wang, Jianlong Chang, Haojie Li, Zhihui Wang, Wanli Ouyang, Qi Tian p64681-64694 from Advances in Neural Information Processing Systems 36
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  • Learning to Predict Structural Vibrations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Predict Structural Vibrations

    Jan Van Delden, Julius Schultz, Christopher Blech, Sabine Langer, Timo Lüddecke p103706-103736 from Advances in Neural Information Processing Systems 37
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  • Learning to Price Homogeneous Data

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Price Homogeneous Data

    Keran Chen, Joon Suk Huh, Kirthevasan Kandasamy p88705-88738 from Advances in Neural Information Processing Systems 37
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  • Learning to Re-Weight Examples with Optimal Transport for Imbalanced Classification

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Re-Weight Examples with Optimal Transport for Imbalanced Classification

    Dandan Guo, Zhuo Li, Meixi Zheng, He Zhao, Mingyuan Zhou, Hongyuan Zha p25517-25530 from Advances in Neural Information Processing Systems 35
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  • Learning to Reason and Memorize with Self-Notes

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Reason and Memorize with Self-Notes

    Jack Lanchantin, Shubham Toshniwal, Jason Weston, Arthur Szlam, Sainbayar Sukhbaatar p11891-11911 from Advances in Neural Information Processing Systems 36
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  • Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Reason Iteratively and Parallelly for Complex Visual Reasoning Scenarios

    Shantanu Jaiswal, Debaditya Roy, Basura Fernando, Cheston Tan p137965-137998 from Advances in Neural Information Processing Systems 37
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  • Learning to Reason via Program Generation, Emulation, and Search

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Reason via Program Generation, Emulation, and Search

    Nathaniel Weir, Muhammad Khalifa, Linlu Qiu, Orion Weller, Peter Clark p36390-36413 from Advances in Neural Information Processing Systems 37
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  • Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Reason with Neural Networks: Generalization, Unseen Data and Boolean Measures

    Emmanuel Abbe, Samy Bengio, Elisabetta Cornacchia, Jon Kleinberg, Aryo Lotfi, Maithra Raghu, Chiyuan Zhang p2709-2722 from Advances in Neural Information Processing Systems 35
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  • Learning to Receive Help: Intervention-Aware Concept Embedding Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Receive Help: Intervention-Aware Concept Embedding Models

    Mateo Espinosa Zarlenga, Katie Collins, Krishnamurthy Dvijotham, Adrian Weller, Zohreh Shams, Mateja Jamnik p37849-37875 from Advances in Neural Information Processing Systems 36
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  • Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Learning to Reconstruct Missing Data from Spatiotemporal Graphs with Sparse Observations

    Ivan Marisca, Andrea Cini, Cesare Alippi p32069-32082 from Advances in Neural Information Processing Systems 35
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