Paper

  • DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DenseFormer: Enhancing Information Flow in Transformers via Depth Weighted Averaging

    Matteo Pagliardini, Amirkeivan Mohtashami, Francois Fleuret, Martin Jaggi p136479-136508 from Advances in Neural Information Processing Systems 37
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  • DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DenseFusion-1M: Merging Vision Experts for Comprehensive Multimodal Perception

    Xiaotong Li, Fan Zhang, Haiwen Diao, Yueze Wang, Xinlong Wang, Ling-Yu Duan p18535-18556 from Advances in Neural Information Processing Systems 37
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  • DENSIFICATION OF NEW ZEALAND-GROWN REDWOOD FOR IMPROVED MECHANICAL PROPERTIES

    World Conference on Timber Engineering 2025

    DENSIFICATION OF NEW ZEALAND-GROWN REDWOOD FOR IMPROVED MECHANICAL PROPERTIES

    Rosie Sargent, Bruce Kenah, Armin Thumm p1611-1619 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
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  • DENSIFIED WOODEN NAIL FOR ADHESIVE- AND METAL- FREE TIMBER ASSEMBLES

    World Conference on Timber Engineering 2023 (WCTE 2023)

    DENSIFIED WOODEN NAIL FOR ADHESIVE- AND METAL- FREE TIMBER ASSEMBLES

    Lei Han, Dusan Pauliny, Anna Sandak, Mariapaola Riggio, Andreja Kutnar, Dick Sandberg, Jakub Sandak p666-670 from World Conference on Timber Engineering (WCTE 2023)
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  • Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Density of States Prediction of Crystalline Materials via Prompt-guided Multi-Modal Transformer

    Namkyeong Lee, Heewoong Noh, Sungwon Kim, Dongmin Hyun, Gyoung S. Na, Chanyoung Park p61678-61698 from Advances in Neural Information Processing Systems 36
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  • Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Density-based User Representation using Gaussian Process Regression for Multi-interest Personalized Retrieval

    Haolun Wu, Ofer Meshi, Masrour Zoghi, Fernando Diaz, Xue Liu, Craig Boutilier, Maryam Karimzadehgan p52568-52594 from Advances in Neural Information Processing Systems 37
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  • Density-Driven Regularization for Out-Of-Distribution Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Density-Driven Regularization for Out-Of-Distribution Detection

    Wenjian Huang, Hao Wang, Jiahao Xia, Chengyan Wang, Jianguo Zhang p887-900 from Advances in Neural Information Processing Systems 35
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  • DePLM: Denoising Protein Language Models for Property Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DePLM: Denoising Protein Language Models for Property Optimization

    Zeyuan Wang, Keyan Ding, Ming Qin, Xiaotong Li, Xiang Zhuang, Yu Zhao, Jianhua Yao, Qiang Zhang, Huajun Chen p75302-75328 from Advances in Neural Information Processing Systems 37
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  • DEPLOYABLE WOOD STRUCTURES FOR DISASTER RELIEF AND MILITARY USE

    World Conference on Timber Engineering 2023 (WCTE 2023)

    DEPLOYABLE WOOD STRUCTURES FOR DISASTER RELIEF AND MILITARY USE

    Jayson Leonard, Weichiang Pang, Michael Stoner, Dustin Albright p3518-3525 from World Conference on Timber Engineering (WCTE 2023)
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  • DEPrune: Depth-wise Separable Convolution Pruning for Maximizing GPU Parallelism

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DEPrune: Depth-wise Separable Convolution Pruning for Maximizing GPU Parallelism

    Cheonjun Park, Mincheol Park, Hyunchan Moon, Myung Kuk Yoon, Seokjin Go, Suhyun Kim, Won Woo Ro p106906-106923 from Advances in Neural Information Processing Systems 37
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  • Depth Anything V2

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Depth Anything V2

    Lihe Yang, Bingyi Kang, Zilong Huang, Zhen Zhao, Xiaogang Xu, Jiashi Feng, Hengshuang Zhao p21875-21911 from Advances in Neural Information Processing Systems 37
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  • Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Depth Anywhere: Enhancing 360 Monocular Depth Estimation via Perspective Distillation and Unlabeled Data Augmentation

    Ning-Hsu Wang, Yu-Lun Liu p127739-127764 from Advances in Neural Information Processing Systems 37
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