Papers
11,015 papers found
DiffAR: Denoising Diffusion Autoregressive Model for Raw Speech Waveform Generation
Roi Benita, Michael Elad, Joseph Keshet
DiffEnc: Variational Diffusion with a Learned Encoder
Beatrix Miranda Ginn Nielsen, Anders Christensen, Andrea Dittadi et al.
Diffeomorphic Mesh Deformation via Efficient Optimal Transport for Cortical Surface Reconstruction
Thanh Tung Le, Khai Nguyen, shanlin sun et al.
Differentiable Euler Characteristic Transforms for Shape Classification
Ernst Röell, Bastian Rieck
Differentiable Learning of Generalized Structured Matrices for Efficient Deep Neural Networks
Changwoo Lee, Hun-Seok Kim
Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach
Xinwei Zhang, Zhiqi Bu, Steven Wu et al.
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni et al.
DIFFTACTILE: A Physics-based Differentiable Tactile Simulator for Contact-rich Robotic Manipulation
Zilin Si, Gu Zhang, Qingwei Ben et al.
Diffusion Generative Flow Samplers: Improving learning signals through partial trajectory optimization
Dinghuai Zhang, Ricky T. Q. Chen, Cheng-Hao Liu et al.
Diffusion in Diffusion: Cyclic One-Way Diffusion for Text-Vision-Conditioned Generation
Ruoyu Wang, Yongqi Yang, Zhihao Qian et al.
Diffusion Model for Dense Matching
Jisu Nam, Gyuseong Lee, Sunwoo Kim et al.
Diffusion Models for Multi-Task Generative Modeling
Changyou Chen, Han Ding, Bunyamin Sisman et al.
DiffusionNAG: Predictor-guided Neural Architecture Generation with Diffusion Models
Sohyun An, Hayeon Lee, Jaehyeong Jo et al.
Diffusion Sampling with Momentum for Mitigating Divergence Artifacts
Suttisak Wizadwongsa, Worameth Chinchuthakun, Pramook Khungurn et al.
DiffusionSat: A Generative Foundation Model for Satellite Imagery
Samar Khanna, Patrick Liu, Linqi Zhou et al.
Diffusion-TS: Interpretable Diffusion for General Time Series Generation
Xinyu Yuan, Yan Qiao
DiLu: A Knowledge-Driven Approach to Autonomous Driving with Large Language Models
Licheng Wen, Daocheng Fu, Xin Li et al.
Directly Fine-Tuning Diffusion Models on Differentiable Rewards
Kevin Clark, Paul Vicol, Kevin Swersky et al.
Dirichlet-based Per-Sample Weighting by Transition Matrix for Noisy Label Learning
HeeSun Bae, Seungjae Shin, Byeonghu Na et al.
Discovering Failure Modes of Text-guided Diffusion Models via Adversarial Search
Qihao Liu, Adam Kortylewski, Yutong Bai et al.
Discovering modular solutions that generalize compositionally
Simon Schug, Seijin Kobayashi, Yassir Akram et al.
Discovering Temporally-Aware Reinforcement Learning Algorithms
Matthew Thomas Jackson, Chris Lu, Louis Kirsch et al.
DisenBooth: Identity-Preserving Disentangled Tuning for Subject-Driven Text-to-Image Generation
Hong Chen, Yipeng Zhang, Simin Wu et al.
Disentangling Time Series Representations via Contrastive Independence-of-Support on l-Variational Inference
Khalid Oublal, Said Ladjal, David Benhaiem et al.