Poster "generative models" Papers
88 papers found • Page 1 of 2
Conference
Adding Conditional Control to Diffusion Models with Reinforcement Learning
Yulai Zhao, Masatoshi Uehara, Gabriele Scalia et al.
Adjoint Matching: Fine-tuning Flow and Diffusion Generative Models with Memoryless Stochastic Optimal Control
Carles Domingo i Enrich, Michal Drozdzal, Brian Karrer et al.
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data
Asad Aali, Giannis Daras, Brett Levac et al.
Are Images Indistinguishable to Humans Also Indistinguishable to Classifiers?
Zebin You, Xinyu Zhang, Hanzhong Guo et al.
Bayesian Experimental Design Via Contrastive Diffusions
Jacopo Iollo, Christophe Heinkelé, Pierre Alliez et al.
Beyond Scores: Proximal Diffusion Models
Zhenghan Fang, Mateo Diaz, Sam Buchanan et al.
CHORDS: Diffusion Sampling Accelerator with Multi-core Hierarchical ODE Solvers
Jiaqi Han, Haotian Ye, Puheng Li et al.
Communication-Efficient Diffusion Denoising Parallelization via Reuse-then-Predict Mechanism
Kunyun Wang, Bohan Li, Kai Yu et al.
Controllable Latent Space Augmentation for Digital Pathology
Sofiène Boutaj, Marin Scalbert, Pierre Marza et al.
Cross-Subject Mind Decoding from Inaccurate Representations
Yangyang Xu, Bangzhen Liu, Wenqi Shao et al.
Detecting Adversarial Data Using Perturbation Forgery
Qian Wang, Chen Li, Yuchen Luo et al.
DiffSim: Taming Diffusion Models for Evaluating Visual Similarity
Yiren Song, Xiaokang Liu, Mike Zheng Shou
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto et al.
Distilled Decoding 2: One-step Sampling of Image Auto-regressive Models with Conditional Score Distillation
Enshu Liu, Qian Chen, Xuefei Ning et al.
DKDM: Data-Free Knowledge Distillation for Diffusion Models with Any Architecture
Qianlong Xiang, Miao Zhang, Yuzhang Shang et al.
DoraCycle: Domain-Oriented Adaptation of Unified Generative Model in Multimodal Cycles
Rui Zhao, Weijia Mao, Mike Zheng Shou
Efficient Multimodal Dataset Distillation via Generative Models
Zhenghao Zhao, Haoxuan Wang, Junyi Wu et al.
Entropic Time Schedulers for Generative Diffusion Models
Dejan Stancevic, Florian Handke, Luca Ambrogioni
ESCA: Enabling Seamless Codec Avatar Execution through Algorithm and Hardware Co-Optimization for Virtual Reality
Mingzhi Zhu, Ding Shang, Sai Qian Zhang
Faster Inference of Flow-Based Generative Models via Improved Data-Noise Coupling
Aram Davtyan, Leello Dadi, Volkan Cevher et al.
FlowRAM: Grounding Flow Matching Policy with Region-Aware Mamba Framework for Robotic Manipulation
Sen Wang, Le Wang, Sanping Zhou et al.
From Search to Sampling: Generative Models for Robust Algorithmic Recourse
Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi
GenHancer: Imperfect Generative Models are Secretly Strong Vision-Centric Enhancers
Shijie Ma, Yuying Ge, Teng Wang et al.
GMValuator: Similarity-based Data Valuation for Generative Models
Jiaxi Yang, Wenlong Deng, Benlin Liu et al.
Image Super-Resolution with Guarantees via Conformalized Generative Models
Eduardo Adame, Daniel Csillag, Guilherme Tegoni Goedert
Improved Discretization Complexity Analysis of Consistency Models: Variance Exploding Forward Process and Decay Discretization Scheme
Ruofeng Yang, Bo Jiang, Cheng Chen et al.
InCoDe: Interpretable Compressed Descriptions For Image Generation
Armand Comas, Aditya Chattopadhyay, Feliu Formosa et al.
Information Theoretic Learning for Diffusion Models with Warm Start
Yirong Shen, Lu GAN, Cong Ling
Knowledge Graph Enhanced Generative Multi-modal Models for Class-Incremental Learning
Xusheng Cao, Haori Lu, Linlan Huang et al.
Learning to Discretize Denoising Diffusion ODEs
Vinh Tong, Trung-Dung Hoang, Anji Liu et al.
Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better
Enshu Liu, Junyi Zhu, Zinan Lin et al.
Localizing Knowledge in Diffusion Transformers
Arman Zarei, Samyadeep Basu, Keivan Rezaei et al.
NeuroRenderedFake: A Challenging Benchmark to Detect Fake Images Generated by Advanced Neural Rendering Methods
Chengdong Dong, B. V. K. Vijaya Kumar, Zhenyu Zhou et al.
Noise Matters: Optimizing Matching Noise for Diffusion Classifiers
Yanghao Wang, Long Chen
NullSwap: Proactive Identity Cloaking Against Deepfake Face Swapping
Tianyi Wang, Shuaicheng Niu, Harry Cheng et al.
One Step Diffusion via Shortcut Models
Kevin Frans, Danijar Hafner, Sergey Levine et al.
On the Relation between Rectified Flows and Optimal Transport
Johannes Hertrich, Antonin Chambolle, Julie Delon
Physics-Constrained Flow Matching: Sampling Generative Models with Hard Constraints
Utkarsh Utkarsh, Pengfei Cai, Alan Edelman et al.
PID-controlled Langevin Dynamics for Faster Sampling on Generative Models
Hongyi Chen, Jianhai Shu, Jingtao Ding et al.
Prioritized Generative Replay
Ren Wang, Kevin Frans, Pieter Abbeel et al.
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
ProtoSnap: Prototype Alignment For Cuneiform Signs
Rachel Mikulinsky, Morris Alper, Shai Gordin et al.
RTDiff: Reverse Trajectory Synthesis via Diffusion for Offline Reinforcement Learning
Qianlan Yang, Yu-Xiong Wang
Señorita-2M: A High-Quality Instruction-based Dataset for General Video Editing by Video Specialists
Bojia Zi, Penghui Ruan, Marco Chen et al.
Stiefel Flow Matching for Moment-Constrained Structure Elucidation
Austin H Cheng, Alston Lo, Kin Long Kelvin Lee et al.
SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints
Miruna Cretu, Charles Harris, Ilia Igashov et al.
Synthetic-powered predictive inference
Meshi Bashari, Roy Maor Lotan, Yonghoon Lee et al.
TARFVAE: Efficient One-Step Generative Time Series Forecasting via TARFLOW based VAE
Jiawen Wei, jiang lan, Pengbo Wei et al.
TeEFusion: Blending Text Embeddings to Distill Classifier-Free Guidance
Minghao Fu, Guo-Hua Wang, Xiaohao Chen et al.
Transformers without Normalization
Jiachen Zhu, Xinlei Chen, Kaiming He et al.