Papers
11,015 papers found
DiffEdit: Diffusion-based semantic image editing with mask guidance
Guillaume Couairon, Jakob Verbeek, Holger Schwenk et al.
Differentiable Mathematical Programming for Object-Centric Representation Learning
Adeel Pervez, Phillip Lippe, Efstratios Gavves
Differentially Private $L_2$-Heavy Hitters in the Sliding Window Model
Jeremiah Blocki, Seunghoon Lee, Tamalika Mukherjee et al.
Differentially Private Adaptive Optimization with Delayed Preconditioners
Tian Li, Manzil Zaheer, Ken Liu et al.
DiffMimic: Efficient Motion Mimicking with Differentiable Physics
Jiawei Ren, Cunjun Yu, Siwei Chen et al.
DIFFormer: Scalable (Graph) Transformers Induced by Energy Constrained Diffusion
Qitian Wu, Chenxiao Yang, Wentao Zhao et al.
DiffuSeq: Sequence to Sequence Text Generation with Diffusion Models
Shansan Gong, Mukai Li, Jiangtao Feng et al.
DiffusER: Diffusion via Edit-based Reconstruction
Machel Reid, Vincent Josua Hellendoorn, Graham Neubig
Diffusion Adversarial Representation Learning for Self-supervised Vessel Segmentation
Boah Kim, Yujin Oh, Jong Chul Ye
Diffusion-based Image Translation using disentangled style and content representation
Gihyun Kwon, Jong Chul Ye
Diffusion-GAN: Training GANs with Diffusion
Zhendong Wang, Huangjie Zheng, Pengcheng He et al.
Diffusion Models Already Have A Semantic Latent Space
Mingi Kwon, Jaeseok Jeong, Youngjung Uh
Diffusion Models for Causal Discovery via Topological Ordering
Pedro Sanchez, Xiao Liu, Alison Q O'Neil et al.
Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning
Zhendong Wang, Jonathan J Hunt, Mingyuan Zhou
Diffusion Posterior Sampling for General Noisy Inverse Problems
Hyungjin Chung, Jeongsol Kim, Michael Thompson Mccann et al.
Diffusion Probabilistic Fields
Peiye Zhuang, Samira Abnar, Jiatao Gu et al.
Diffusion Probabilistic Modeling of Protein Backbones in 3D for the motif-scaffolding problem
Brian L. Trippe, Jason Yim, Doug Tischer et al.
DiGress: Discrete Denoising diffusion for graph generation
Clement Vignac, Igor Krawczuk, Antoine Siraudin et al.
Dilated convolution with learnable spacings
Ismail Khalfaoui Hassani, Thomas Pellegrini, Timothée Masquelier
Diminishing Return of Value Expansion Methods in Model-Based Reinforcement Learning
Daniel Palenicek, Michael Lutter, Joao Carvalho et al.
DINO as a von Mises-Fisher mixture model
Hariprasath Govindarajan, Per Sidén, Jacob Roll et al.
DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection
Hao Zhang, Feng Li, Shilong Liu et al.
Direct Embedding of Temporal Network Edges via Time-Decayed Line Graphs
Sudhanshu Chanpuriya, Ryan A. Rossi, Sungchul Kim et al.
Dirichlet-based Uncertainty Calibration for Active Domain Adaptation
Mixue Xie, Shuang Li, Rui Zhang et al.