ICLR Papers
6,124 papers found • Page 18 of 123
DiffPuter: Empowering Diffusion Models for Missing Data Imputation
Hengrui Zhang, Liancheng Fang, Qitian Wu et al.
DiffSplat: Repurposing Image Diffusion Models for Scalable Gaussian Splat Generation
Chenguo Lin, Panwang Pan, Bangbang Yang et al.
Diffusing States and Matching Scores: A New Framework for Imitation Learning
Runzhe Wu, Yiding Chen, Gokul Swamy et al.
Diffusing to the Top: Boost Graph Neural Networks with Minimal Hyperparameter Tuning
Lequan Lin, Dai Shi, Andi Han et al.
Diffusion$^2$: Dynamic 3D Content Generation via Score Composition of Video and Multi-view Diffusion Models
Zeyu Yang, Zijie Pan, Chun Gu et al.
Diffusion Actor-Critic: Formulating Constrained Policy Iteration as Diffusion Noise Regression for Offline Reinforcement Learning
Linjiajie Fang, Ruoxue Liu, Jing Zhang et al.
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models
Jinxu Lin, Linwei Tao, Minjing Dong et al.
Diffusion-based Decoupled Deterministic and Uncertain Framework for Probabilistic Multivariate Time Series Forecasting
Qi Li, Zhenyu Zhang, Lei Yao et al.
Diffusion-based Neural Network Weights Generation
Bedionita Soro, Bruno Andreis, Hayeon Lee et al.
Diffusion-Based Planning for Autonomous Driving with Flexible Guidance
Yinan Zheng, Ruiming Liang, Kexin ZHENG et al.
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park et al.
Diffusion Bridge Implicit Models
Kaiwen Zheng, Guande He, Jianfei Chen et al.
Diffusion Feedback Helps CLIP See Better
Wenxuan Wang, Quan Sun, Fan Zhang et al.
Diffusion Generative Modeling for Spatially Resolved Gene Expression Inference from Histology Images
Sichen Zhu, Yuchen Zhu, Molei Tao et al.
DiffusionGuard: A Robust Defense Against Malicious Diffusion-based Image Editing
William June Suk Choi, Kyungmin Lee, Jongheon Jeong et al.
Diffusion Models and Gaussian Flow Matching: Two Sides of the Same Coin
Ruiqi Gao, Emiel Hoogeboom, Jonathan Heek et al.
Diffusion Models are Evolutionary Algorithms
Yanbo Zhang, Benedikt Hartl, Hananel Hazan et al.
Diffusion Models Are Real-Time Game Engines
Dani Valevski, Yaniv Leviathan, Moab Arar et al.
Diffusion Models as Cartoonists: The Curious Case of High Density Regions
Rafał Karczewski, Markus Heinonen, Vikas Garg
Diffusion-NPO: Negative Preference Optimization for Better Preference Aligned Generation of Diffusion Models
Fu-Yun Wang, Yunhao Shui, Jingtan Piao et al.
Diffusion On Syntax Trees For Program Synthesis
Shreyas Kapur, Erik Jenner, Stuart Russell
Diffusion Policy Policy Optimization
Allen Ren, Justin Lidard, Lars Ankile et al.
Diffusion State-Guided Projected Gradient for Inverse Problems
Rayhan Zirvi, Bahareh Tolooshams, anima anandkumar
Diffusion Transformer Captures Spatial-Temporal Dependencies: A Theory for Gaussian Process Data
Hengyu Fu, Zehao Dou, Jiawei Guo et al.
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto et al.
Digi-Q: Learning VLM Q-Value Functions for Training Device-Control Agents
Hao Bai, Yifei Zhou, Li Li et al.
Dimension Agnostic Neural Processes
Hyungi Lee, Chaeyun Jang, Dong Bok Lee et al.
DINOv2: Learning Robust Visual Features without Supervision
Pierre Fernandez, Piotr Bojanowski, Gabriel Synnaeve et al.
Direct Distributional Optimization for Provable Alignment of Diffusion Models
Ryotaro Kawata, Kazusato Oko, Atsushi Nitanda et al.
Directional Gradient Projection for Robust Fine-Tuning of Foundation Models
Chengyue Huang, Junjiao Tian, Brisa Maneechotesuwan et al.
Direct Post-Training Preference Alignment for Multi-Agent Motion Generation Model Using Implicit Feedback from Pre-training Demonstrations
Thomas Tian, Kratarth Goel
Discovering Clone Negatives via Adaptive Contrastive Learning for Image-Text Matching
Renjie Pan, Jihao Dong, Hua Yang
Discovering Group Structures via Unitary Representation Learning
Dongsung Huh
Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi et al.
Discovering Temporally Compositional Neural Manifolds with Switching Infinite GPFA
Changmin Yu, Maneesh Sahani, Máté Lengyel
DiscoveryBench: Towards Data-Driven Discovery with Large Language Models
Bodhisattwa Prasad Majumder, Harshit Surana, Dhruv Agarwal et al.
Discrete Codebook World Models for Continuous Control
Aidan Scannell, Mohammadreza Nakhaeinezhadfard, Kalle Kujanpää et al.
Discrete Copula Diffusion
Anji Liu, Oliver Broadrick, Mathias Niepert et al.
Discrete Diffusion Schrödinger Bridge Matching for Graph Transformation
Jun Hyeong Kim, Seonghwan Kim, Seokhyun Moon et al.
Discrete Distribution Networks
Lei Yang
Discrete GCBF Proximal Policy Optimization for Multi-agent Safe Optimal Control
Songyuan Zhang, Oswin So, Mitchell Black et al.
Discrete Latent Plans via Semantic Skill Abstractions
Haobin Jiang, Wang, Zongqing Lu
Discretization-invariance? On the Discretization Mismatch Errors in Neural Operators
Wenhan Gao, Ruichen Xu, Yuefan Deng et al.
Discriminating image representations with principal distortions
Jenelle Feather, David Lipshutz, Sarah Harvey et al.
Discriminator-Guided Embodied Planning for LLM Agent
Haofu Qian, Chenjia Bai, Jiatao Zhang et al.
Disentangled Representation Learning with the Gromov-Monge Gap
Théo Uscidda, Luca Eyring, Karsten Roth et al.
Disentangling 3D Animal Pose Dynamics with Scrubbed Conditional Latent Variables
Joshua Wu, Hari Koneru, James Ravenel et al.
Disentangling Representations through Multi-task Learning
Pantelis Vafidis, Aman Bhargava, Antonio Rangel
DisEnvisioner: Disentangled and Enriched Visual Prompt for Customized Image Generation
Jing He, Haodong Li, huyongzhe et al.
DiSK: Differentially Private Optimizer with Simplified Kalman Filter for Noise Reduction
Xinwei Zhang, Zhiqi Bu, Borja Balle et al.