Paper

  • Exponential Quantum Communication Advantage in Distributed Inference and Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exponential Quantum Communication Advantage in Distributed Inference and Learning

    Dar Gilboa, Hagay Michaeli, Daniel Soudry, Jarrod McClean p30425-30473 from Advances in Neural Information Processing Systems 37
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  • Exponential Separations in Symmetric Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exponential Separations in Symmetric Neural Networks

    Aaron Zweig, Joan Bruna p33134-33145 from Advances in Neural Information Processing Systems 35
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  • Exponentially Convergent Algorithms for Supervised Matrix Factorization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exponentially Convergent Algorithms for Supervised Matrix Factorization

    Joowon Lee, Hanbaek Lyu, Weixin Yao p76947-76959 from Advances in Neural Information Processing Systems 36
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  • Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exponentially Improving the Complexity of Simulating the Weisfeiler-Lehman Test with Graph Neural Networks

    Anders Aamand, Justin Chen, Piotr Indyk, Shyam Narayanan, Ronitt Rubinfeld, Nicholas Schiefer, Sandeep Silwal, Tal Wagner p27333-27346 from Advances in Neural Information Processing Systems 35
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  • Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exposing and Exploiting Fine-Grained Block Structures for Fast and Accurate Sparse Training

    Peng Jiang, Lihan Hu, Shihui Song p38345-38357 from Advances in Neural Information Processing Systems 35
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  • Exposing Attention Glitches with Flip-Flop Language Modeling

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exposing Attention Glitches with Flip-Flop Language Modeling

    Bingbin Liu, Jordan Ash, Surbhi Goel, Akshay Krishnamurthy, Cyril Zhang p25549-25583 from Advances in Neural Information Processing Systems 36
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  • Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Exposing flaws of generative model evaluation metrics and their unfair treatment of diffusion models

    George Stein, Jesse Cresswell, Rasa Hosseinzadeh, Yi Sui, Brendan Ross, Valentin Villecroze, Zhaoyan Liu, Anthony Caterini, Eric Taylor, Gabriel Loaiza-Ganem p3732-3784 from Advances in Neural Information Processing Systems 36
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  • Expressive Gaussian Human Avatars from Monocular RGB Video

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Expressive Gaussian Human Avatars from Monocular RGB Video

    Hezhen Hu, Zhiwen Fan, Tianhao Wu, Yihan Xi, Seoyoung Lee, Georgios Pavlakos, Zhangyang Wang p5646-5660 from Advances in Neural Information Processing Systems 37
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  • Expressive probabilistic sampling in recurrent neural networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Expressive probabilistic sampling in recurrent neural networks

    Shirui Chen, Linxing Jiang, Rajesh Pn Rao, Eric Shea-Brown p34981-35005 from Advances in Neural Information Processing Systems 36
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  • Expressive Sign Equivariant Networks for Spectral Geometric Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Expressive Sign Equivariant Networks for Spectral Geometric Learning

    Derek Lim, Joshua Robinson, Stefanie Jegelka, Haggai Maron p16426-16455 from Advances in Neural Information Processing Systems 36
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  • Expressivity-Preserving GNN Simulation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Expressivity-Preserving GNN Simulation

    Fabian Jogl, Maximilian Thiessen, Thomas Gärtner p74544-74581 from Advances in Neural Information Processing Systems 36
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  • ExPT: Synthetic Pretraining for Few-Shot Experimental Design

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    ExPT: Synthetic Pretraining for Few-Shot Experimental Design

    Tung Nguyen, Sudhanshu Agrawal, Aditya Grover p45856-45869 from Advances in Neural Information Processing Systems 36
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