Paper

  • Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Geometry Cloak: Preventing TGS-based 3D Reconstruction from Copyrighted Images

    Ka Chun Cheung, Ziyuan Luo, Simon See, Qi Song, Renjie Wan p119361-119385 from Advances in Neural Information Processing Systems 37
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  • Geometry of naturalistic object representations in recurrent neural network models of working memory

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Geometry of naturalistic object representations in recurrent neural network models of working memory

    Pouya Bashivan, Takuya Ito, Xiaoxuan Lei p100604-100629 from Advances in Neural Information Processing Systems 37
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  • Geometry-Aware Adaptation for Pretrained Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Geometry-Aware Adaptation for Pretrained Models

    Dyah Adila, Sonia Cromp, Tzu-Heng Huang, Xintong Li, Nicholas Roberts, Frederic Sala, Jitian Zhao p49628-49658 from Advances in Neural Information Processing Systems 36
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  • Geometry-aware training of factorized layers in tensor Tucker format

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Geometry-aware training of factorized layers in tensor Tucker format

    Gianluca Ceruti, Jonas Kusch, Steffen Schotthöfer, Francesco Tudisco, Emanuele Zangrando p129743-129773 from Advances in Neural Information Processing Systems 37
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  • Geometry-Aware Two-Scale PIFu Representation for Human Reconstruction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Geometry-Aware Two-Scale PIFu Representation for Human Reconstruction

    Hujun Bao, Zheng Dong, Ziheng Duan, Rynson Lau, Ke Xu, Weiwei Xu p31130-31144 from Advances in Neural Information Processing Systems 35
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  • Geometry-Informed Neural Operator for Large-Scale 3D PDEs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Geometry-Informed Neural Operator for Large-Scale 3D PDEs

    Animashree Anandkumar, Kamyar Azizzadenesheli, Chris Choy, Christian Hundt, Jean Kossaifi, Nikola Kovachki, Boyi Li, Zongyi Li, Mohammad Amin Nabian, Shourya Otta, Maximilian Stadler p35836-35854 from Advances in Neural Information Processing Systems 36
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  • GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GeoNLF: Geometry guided Pose-Free Neural LiDAR Fields

    Guang Chen, Changjun Jiang, Fan Lu, Haiyun Wei, Weiyi Xue, Zehan Zheng p73672-73692 from Advances in Neural Information Processing Systems 37
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  • GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GeoPhy: Differentiable Phylogenetic Inference via Geometric Gradients of Tree Topologies

    Michiaki Hamada, Takahiro Mimori p36591-36619 from Advances in Neural Information Processing Systems 36
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  • GeoPlant: Spatial Plant Species Prediction Dataset

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GeoPlant: Spatial Plant Species Prediction Dataset

    Pierre Bonnet, Christophe Botella, Benjamin Deneu, Alexis Joly, Théo Larcher, César Leblanc, Diego Marcos, Rémi Palard, Lukas Picek, Maximilien Servajean p126653-126676 from Advances in Neural Information Processing Systems 37
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  • GEOSTAR SYSTEMS: ADVANCEMENTS IN BOREHOLE HEAT EXCHANGER TECHNOLOGY FOR URBAN HEAT TRANSITIONS - MONITORING AND FUTURE DEVELOPMENTS

    ECOS 2024

    GEOSTAR SYSTEMS: ADVANCEMENTS IN BOREHOLE HEAT EXCHANGER TECHNOLOGY FOR URBAN HEAT TRANSITIONS - MONITORING AND FUTURE DEVELOPMENTS

    Michael Rath, Timm Eicker, Holger Born, Jonas Güldenhaupt, Gregor Bussmann, Rolf Bracke p2388-2399 from 37th International Conference on Efficiency, Cost, Optimization, Simulation and Environmental Impact of Energy Systems (ECOS 2024)
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  • GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GeoTMI: Predicting Quantum Chemical Property with Easy-to-Obtain Geometry via Positional Denoising

    Hyeonsu Kim, Jun Hyeong Kim, Woo Youn Kim, Seonghwan Kim, Seokhyun Moon, Jeheon Woo p46027-46040 from Advances in Neural Information Processing Systems 36
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  • GEQ: Gaussian Kernel Inspired Equilibrium Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    GEQ: Gaussian Kernel Inspired Equilibrium Models

    Mingjie Li, Zhouchen Lin, Yisen Wang p38767-38785 from Advances in Neural Information Processing Systems 36
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