Neural Information Processing Systems Foundation, Inc. (NeurIPS)

  • DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepACO: Neural-enhanced Ant Systems for Combinatorial Optimization

    Haoran Ye, Jiarui Wang, Zhiguang Cao, Helan Liang, Yong Li p43706-43728 from Advances in Neural Information Processing Systems 36
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  • DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepDRK: Deep Dependency Regularized Knockoff for Feature Selection

    Hongyu Shen, Yici Yan, Zhizhen Zhao p7981-8013 from Advances in Neural Information Processing Systems 37
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  • DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepfakeBench: A Comprehensive Benchmark of Deepfake Detection

    Zhiyuan Yan, Yong Zhang, Xinhang Yuan, Siwei Lyu, Baoyuan Wu p4534-4565 from Advances in Neural Information Processing Systems 36
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  • DeepFoids: Adaptive Bio-Inspired Fish Simulation with Deep Reinforcement Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepFoids: Adaptive Bio-Inspired Fish Simulation with Deep Reinforcement Learning

    Yuko Ishiwaka, Xiao Zeng, Shun Ogawa, Donovan Westwater, Tadayuki Tone, Masaki Nakada p18377-18389 from Advances in Neural Information Processing Systems 35
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  • DeepInteraction: 3D Object Detection Via Modality Interaction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepInteraction: 3D Object Detection Via Modality Interaction

    Zeyu Yang, Jiaqi Chen, Zhenwei Miao, Wei Li, Xiatian Zhu, Li Zhang p1992-2005 from Advances in Neural Information Processing Systems 35
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  • DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepITE: Designing Variational Graph Autoencoders for Intervention Target Estimation

    Hongyuan Tao, Hang Yu, Jianguo Li p89978-90008 from Advances in Neural Information Processing Systems 37
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  • DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepLag: Discovering Deep Lagrangian Dynamics for Intuitive Fluid Prediction

    Qilong Ma, Haixu Wu, Lanxiang Xing, Shangchen Miao, Mingsheng Long p122833-122866 from Advances in Neural Information Processing Systems 37
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  • DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepMed: Semiparametric Causal Mediation Analysis with Debiased Deep Learning

    Siqi Xu, Lin Liu, Zhonghua Liu p28238-28251 from Advances in Neural Information Processing Systems 35
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  • DeepPCR: Parallelizing Sequential Operations in Neural Networks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepPCR: Parallelizing Sequential Operations in Neural Networks

    Federico Danieli, Miguel Sarabia, Xavier Suau Cuadros, Pau Rodriguez, Luca Zappella p47598-47625 from Advances in Neural Information Processing Systems 36
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  • DeepSimHO: Stable Pose Estimation for Hand-Object Interaction via Physics Simulation

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepSimHO: Stable Pose Estimation for Hand-Object Interaction via Physics Simulation

    Rong Wang, Wei Mao, Hongdong Li p79685-79697 from Advances in Neural Information Processing Systems 36
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  • DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepStack: Deeply Stacking Visual Tokens is Surprisingly Simple and Effective for LMMs

    Lingchen Meng, Jianwei Yang, Rui Tian, Xiyang Dai, Zuxuan Wu, Jianfeng Gao, Yu-Gang Jiang p23464-23487 from Advances in Neural Information Processing Systems 37
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  • DeepTOP: Deep Threshold-Optimal Policy for MDPs and RMABs

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeepTOP: Deep Threshold-Optimal Policy for MDPs and RMABs

    Khaled Nakhleh, I-Hong Hou p28734-28746 from Advances in Neural Information Processing Systems 35
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  • DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeeR-VLA: Dynamic Inference of Multimodal Large Language Models for Efficient Robot Execution

    Yang Yue, Yulin Wang, Bingyi Kang, Yizeng Han, Shenzhi Wang, Shiji Song, Jiashi Feng, Gao Huang p56619-56643 from Advances in Neural Information Processing Systems 37
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  • Defending Against Adversarial Attacks Via Neural Dynamic System

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Defending Against Adversarial Attacks Via Neural Dynamic System

    Xiyuan Li, Zou Xin, Weiwei Liu p6372-6383 from Advances in Neural Information Processing Systems 35
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  • Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Defending against Data-Free Model Extraction by Distributionally Robust Defensive Training

    Zhenyi Wang, Li Shen, Tongliang Liu, Tiehang Duan, Yanjun Zhu, Donglin Zhan, David Doermann, Mingchen Gao p624-637 from Advances in Neural Information Processing Systems 36
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  • Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Defending Pre-trained Language Models as Few-shot Learners against Backdoor Attacks

    Zhaohan Xi, Tianyu Du, Changjiang Li, Ren Pang, Shouling Ji, Jinghui Chen, Fenglong Ma, Ting Wang p32748-32764 from Advances in Neural Information Processing Systems 36
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  • Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models

    Yimeng Zhang, Xin Chen, Jinghan Jia, Yihua Zhang, Chongyu Fan, Jiancheng Liu, Mingyi Hong, Ke Ding, Sijia Liu p36748-36776 from Advances in Neural Information Processing Systems 37
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  • Defining and Characterizing Reward Hacking

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Defining and Characterizing Reward Hacking

    Joar Skalse, Nikolaus Howe, Dmitrii Krasheninnikov, David Krueger p9460-9471 from Advances in Neural Information Processing Systems 35
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  • DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeformableTST: Transformer for Time Series Forecasting without Over-reliance on Patching

    Donghao Luo, Xue Wang p88003-88044 from Advances in Neural Information Processing Systems 37
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  • DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform

    Alexander Denker, Francisco Vargas, Shreyas Padhy, Kieran Didi, Simon Mathis, Vincent Dutordoir, Riccardo Barbano, Emile Mathieu, Urszula Komorowska, Pietro Lio p19636-19682 from Advances in Neural Information Processing Systems 37
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  • Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Degradation-Aware Unfolding Half-Shuffle Transformer for Spectral Compressive Imaging

    Yuanhao Cai, Jing Lin, Haoqian Wang, Xin Yuan, Henghui Ding, Yulun Zhang, Radu Timofte, Luc V Gool p37749-37761 from Advances in Neural Information Processing Systems 35
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  • Degraded Polygons Raise Fundamental Questions of Neural Network Perception

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Degraded Polygons Raise Fundamental Questions of Neural Network Perception

    Leonard Tang, Dan Ley p9695-9706 from Advances in Neural Information Processing Systems 36
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  • DeiSAM: Segment Anything with Deictic Prompting

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    DeiSAM: Segment Anything with Deictic Prompting

    Hikaru Shindo, Manuel Brack, Gopika Sudhakaran, Devendra Dhami, Patrick Schramowski, Kristian Kersting p52266-52295 from Advances in Neural Information Processing Systems 37
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  • Déjà Vu Memorization in Vision–Language Models

    Neural Information Processing Systems Foundation, Inc. (NeurIPS)

    Déjà Vu Memorization in Vision–Language Models

    Bargav Jayaraman, Chuan Guo, Kamalika Chaudhuri p50722-50749 from Advances in Neural Information Processing Systems 37
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