Paper

  • 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

    Seokjin Go, Suhyun Kim, Hyunchan Moon, Cheonjun Park, Mincheol Park, Won Woo Ro, Myung Kuk Yoon p106906-106923 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • Depth Anything V2

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Depth Anything V2

    Jiashi Feng, Zilong Huang, Bingyi Kang, Xiaogang Xu, Lihe Yang, Hengshuang Zhao, Zhen Zhao p21875-21911 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • 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

    Yu-Lun Liu, Ning-Hsu Wang p127739-127764 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • Depth is More Powerful than Width with Prediction Concatenation in Deep Forest

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Depth is More Powerful than Width with Prediction Concatenation in Deep Forest

    Yi-Xiao He, Shen-Huan Lyu, Zhi-Hua Zhou p29719-29732 from Advances in Neural Information Processing Systems 35
    Our Price: $0.00
  • Depth-discriminative Metric Learning for Monocular 3D Object Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Depth-discriminative Metric Learning for Monocular 3D Object Detection

    Wonhyeok Choi, Sunghoon Im, Mingyu Shin p80165-80177 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • Derandomized novelty detection with FDR control via conformal e-values

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Derandomized novelty detection with FDR control via conformal e-values

    Meshi Bashari, Amir Epstein, Yaniv Romano, Matteo Sesia p65585-65596 from Advances in Neural Information Processing Systems 36
    Our Price: $0.00
  • Derandomizing Multi-Distribution Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Derandomizing Multi-Distribution Learning

    Kasper Green Larsen, Omar Montasser, Nikita Zhivotovskiy p94246-94264 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • DERIVATION FROM EN927 METHOD FOR EVALUATING OUTDOOR DURABILITY OF COATED FIRE-RETARDANT-TREATED WOOD

    World Conference on Timber Engineering 2023 (WCTE 2023)

    DERIVATION FROM EN927 METHOD FOR EVALUATING OUTDOOR DURABILITY OF COATED FIRE-RETARDANT-TREATED WOOD

    Ryo Takase, Atsuko Ishikawa, Daisuke Kamikawa p505-511 from World Conference on Timber Engineering (WCTE 2023)
    Our Price: $0.00
  • DERIVATION OF SHEAR MODULUS OF THE RPF ADHESIVE LAYER IN BLOCK SHEAR TESTS USING DIGITAL IMAGE CORRELATION

    World Conference on Timber Engineering 2025

    DERIVATION OF SHEAR MODULUS OF THE RPF ADHESIVE LAYER IN BLOCK SHEAR TESTS USING DIGITAL IMAGE CORRELATION

    Koki Kawano, Kohta Miyamoto, Kenji Aoki p297-302 from 14th World Conference on Timber Engineering 2025 (WCTE 2025)
    Our Price: $0.00
  • Derivative-enhanced Deep Operator Network

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Derivative-enhanced Deep Operator Network

    Nolan Bridges, Peng Chen, Yuan Qiu p20945-20981 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • Derivatives of Stochastic Gradient Descent in parametric optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Derivatives of Stochastic Gradient Descent in parametric optimization

    Franck Iutzeler, Edouard Pauwels, Samuel Vaiter p118859-118882 from Advances in Neural Information Processing Systems 37
    Our Price: $0.00
  • Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Descent Steps of a Relation-Aware Energy Produce Heterogeneous Graph Neural Networks

    Hongjoon Ahn, Quan Gan, Taesup Moon, David P Wipf, Yongyi Yang p38436-38448 from Advances in Neural Information Processing Systems 35
    Our Price: $0.00