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

    Zhiguang Cao, Yong Li, Helan Liang, Jiarui Wang, Haoran Ye 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

    Siwei Lyu, Baoyuan Wu, Zhiyuan Yan, Xinhang Yuan, Yong Zhang 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, Masaki Nakada, Shun Ogawa, Tadayuki Tone, Donovan Westwater, Xiao Zeng 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

    Jiaqi Chen, Wei Li, Zhenwei Miao, Zeyu Yang, Li Zhang, Xiatian Zhu 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

    Jianguo Li, Hongyuan Tao, Hang Yu 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

    Mingsheng Long, Qilong Ma, Shangchen Miao, Haixu Wu, Lanxiang Xing 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

    Lin Liu, Zhonghua Liu, Siqi Xu 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, Pau Rodriguez, Miguel Sarabia, Xavier Suau Cuadros, 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

    Hongdong Li, Wei Mao, Rong Wang 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

    Xiyang Dai, Jianfeng Gao, Yu-Gang Jiang, Lingchen Meng, Rui Tian, Zuxuan Wu, Jianwei Yang 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

    I-Hong Hou, Khaled Nakhleh 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

    Jiashi Feng, Yizeng Han, Gao Huang, Bingyi Kang, Shiji Song, Shenzhi Wang, Yulin Wang, Yang Yue 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, Weiwei Liu, Zou Xin 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

    David Doermann, Tiehang Duan, Mingchen Gao, Tongliang Liu, Li Shen, Zhenyi Wang, Donglin Zhan, Yanjun Zhu 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

    Jinghui Chen, Tianyu Du, Shouling Ji, Changjiang Li, Fenglong Ma, Ren Pang, Ting Wang, Zhaohan Xi 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

    Xin Chen, Ke Ding, Chongyu Fan, Mingyi Hong, Jinghan Jia, Jiancheng Liu, Sijia Liu, Yihua Zhang, Yimeng Zhang 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

    Nikolaus Howe, Dmitrii Krasheninnikov, David Krueger, Joar Skalse 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

    Riccardo Barbano, Alexander Denker, Kieran Didi, Vincent Dutordoir, Urszula Komorowska, Pietro Lio, Emile Mathieu, Simon Mathis, Shreyas Padhy, Francisco Vargas 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, Henghui Ding, Luc V Gool, Jing Lin, Radu Timofte, Haoqian Wang, Xin Yuan, Yulun Zhang 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

    Dan Ley, Leonard Tang 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

    Manuel Brack, Devendra Dhami, Kristian Kersting, Patrick Schramowski, Hikaru Shindo, Gopika Sudhakaran 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

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