Paper

  • Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Discriminative Feature Attributions: Bridging Post Hoc Explainability and Inherent Interpretability

    Usha Bhalla, Suraj Srinivas, Himabindu Lakkaraju p44105-44122 from Advances in Neural Information Processing Systems 36
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  • DISCS: A Benchmark for Discrete Sampling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DISCS: A Benchmark for Discrete Sampling

    Katayoon Goshvadi, Haoran Sun, Xingchao Liu, Azade Nova, Ruqi Zhang, Will Grathwohl, Dale Schuurmans, Hanjun Dai p79035-79066 from Advances in Neural Information Processing Systems 36
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  • DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DisDiff: Unsupervised Disentanglement of Diffusion Probabilistic Models

    Tao Yang, Yuwang Wang, Yan Lu, Nanning Zheng p69130-69156 from Advances in Neural Information Processing Systems 36
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  • DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DisenGCD: A Meta Multigraph-assisted Disentangled Graph Learning Framework for Cognitive Diagnosis

    Shangshang Yang, Mingyang Chen, Ziwen Wang, Xiaoshan Yu, Panpan Zhang, Haiping Ma, Xingyi Zhang p91532-91559 from Advances in Neural Information Processing Systems 37
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  • Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangled Counterfactual Learning for Physical Audiovisual Commonsense Reasoning

    Changsheng Lv, Shuai Zhang, Yapeng Tian, Mengshi Qi, Huadong Ma p12476-12488 from Advances in Neural Information Processing Systems 36
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  • Disentangled Representation Learning in Non-Markovian Causal Systems

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangled Representation Learning in Non-Markovian Causal Systems

    Adam Li, Yushu Pan, Elias Bareinboim p104843-104903 from Advances in Neural Information Processing Systems 37
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  • Disentangled Style Domain for Implicit $z$-Watermark Towards Copyright Protection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangled Style Domain for Implicit $z$-Watermark Towards Copyright Protection

    Junqiang Huang, Zhaojun Guo, Ge Luo, Zhenxing Qian, Sheng Li, Xinpeng Zhang p55810-55830 from Advances in Neural Information Processing Systems 37
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  • Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangled Unsupervised Skill Discovery for Efficient Hierarchical Reinforcement Learning

    Jiaheng Hu, Zizhao Wang, Peter Stone, Roberto Martín-Martín p76529-76552 from Advances in Neural Information Processing Systems 37
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  • Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangled Wasserstein Autoencoder for T-Cell Receptor Engineering

    Tianxiao Li, Hongyu Guo, Filippo Grazioli, Mark Gerstein, Martin Renqiang Min p73604-73632 from Advances in Neural Information Processing Systems 36
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  • Disentanglement via Latent Quantization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentanglement via Latent Quantization

    Kyle Hsu, William Dorrell, James Whittington, Jiajun Wu, Chelsea Finn p45463-45488 from Advances in Neural Information Processing Systems 36
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  • Disentangling and mitigating the impact of task similarity for continual learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangling and mitigating the impact of task similarity for continual learning

    Naoki Hiratani p3243-3274 from Advances in Neural Information Processing Systems 37
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  • Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Disentangling Causal Effects from Sets of Interventions in the Presence of Unobserved Confounders

    Olivier Jeunen, Ciarán Gilligan-Lee, Rishabh Mehrotra, Mounia Lalmas p27850-27861 from Advances in Neural Information Processing Systems 35
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