Papers
11,015 papers found
DEGREE: Decomposition Based Explanation for Graph Neural Networks
Qizhang Feng, Ninghao Liu, Fan Yang et al.
Delaunay Component Analysis for Evaluation of Data Representations
Petra Poklukar, Vladislav Polianskii, Anastasiia Varava et al.
DemoDICE: Offline Imitation Learning with Supplementary Imperfect Demonstrations
Geon-Hyeong Kim, Seokin Seo, Jongmin Lee et al.
Demystifying Batch Normalization in ReLU Networks: Equivalent Convex Optimization Models and Implicit Regularization
Tolga Ergen, Arda Sahiner, Batu Ozturkler et al.
Demystifying Limited Adversarial Transferability in Automatic Speech Recognition Systems
Hadi Abdullah, Aditya Karlekar, Vincent Bindschaedler et al.
Denoising Likelihood Score Matching for Conditional Score-based Data Generation
Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng et al.
DEPTS: Deep Expansion Learning for Periodic Time Series Forecasting
Wei Fan, Shun Zheng, Xiaohan Yi et al.
DeSKO: Stability-Assured Robust Control with a Deep Stochastic Koopman Operator
Minghao Han, Jacob Euler-Rolle, Robert K. Katzschmann
DictFormer: Tiny Transformer with Shared Dictionary
Qian Lou, Ting Hua, Yen-Chang Hsu et al.
Differentiable DAG Sampling
Bertrand Charpentier, Simon Kibler, Stephan Günnemann
Differentiable Gradient Sampling for Learning Implicit 3D Scene Reconstructions from a Single Image
Shizhan Zhu, Sayna Ebrahimi, Angjoo Kanazawa et al.
Differentiable Prompt Makes Pre-trained Language Models Better Few-shot Learners
Ningyu Zhang, Luoqiu Li, Xiang Chen et al.
Differentiable Scaffolding Tree for Molecule Optimization
Tianfan Fu, Wenhao Gao, Cao Xiao et al.
Differentially Private Fine-tuning of Language Models
Da Yu, Saurabh Naik, Arturs Backurs et al.
Differentially Private Fractional Frequency Moments Estimation with Polylogarithmic Space
Lun Wang, Iosif Pinelis, Dawn Song
DiffSkill: Skill Abstraction from Differentiable Physics for Deformable Object Manipulations with Tools
Xingyu Lin, Zhiao Huang, Yunzhu Li et al.
Diffusion-Based Voice Conversion with Fast Maximum Likelihood Sampling Scheme
Vadim Popov, Ivan Vovk, Vladimir Gogoryan et al.
Direct then Diffuse: Incremental Unsupervised Skill Discovery for State Covering and Goal Reaching
Pierre-Alexandre Kamienny, Jean Tarbouriech, sylvain lamprier et al.
DISCOVERING AND EXPLAINING THE REPRESENTATION BOTTLENECK OF DNNS
Huiqi Deng, Qihan Ren, Hao Zhang et al.
Discovering Invariant Rationales for Graph Neural Networks
Yingxin Wu, Xiang Wang, An Zhang et al.
Discovering Latent Concepts Learned in BERT
Fahim Dalvi, Abdul Rafae Khan, Firoj Alam et al.
Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
Chengping Rao, Pu Ren, Yang Liu et al.
Discrepancy-Based Active Learning for Domain Adaptation
Antoine de Mathelin, François Deheeger, Mathilde MOUGEOT et al.
Discrete Representations Strengthen Vision Transformer Robustness
Chengzhi Mao, Lu Jiang, Mostafa Dehghani et al.