"generative modeling" Papers
63 papers found • Page 1 of 2
A Black-Box Debiasing Framework for Conditional Sampling
Han Cui, Jingbo Liu
Ambient Diffusion Omni: Training Good Models with Bad Data
Giannis Daras, Adrian Rodriguez-Munoz, Adam Klivans et al.
Assessing the quality of denoising diffusion models in Wasserstein distance: noisy score and optimal bounds
Vahan Arsenyan, Elen Vardanyan, Arnak Dalalyan
CDFlow: Building Invertible Layers with Circulant and Diagonal Matrices
XUCHEN FENG, Siyu Liao
Conformal Generative Modeling with Improved Sample Efficiency through Sequential Greedy Filtering
Klaus-Rudolf Kladny, Bernhard Schölkopf, Michael Muehlebach
Contextual Thompson Sampling via Generation of Missing Data
Kelly W Zhang, Tianhui Cai, Hongseok Namkoong et al.
Continuous Diffusion for Mixed-Type Tabular Data
Markus Mueller, Kathrin Gruber, Dennis Fok
Cross-fluctuation phase transitions reveal sampling dynamics in diffusion models
Sai Niranjan Ramachandran, Manish Krishan Lal, Suvrit Sra
Diffusion Bridge AutoEncoders for Unsupervised Representation Learning
Yeongmin Kim, Kwanghyeon Lee, Minsang Park et al.
Efficient Distribution Matching of Representations via Noise-Injected Deep InfoMax
Ivan Butakov, Alexander Semenenko, Alexander Tolmachev et al.
Energy Matching: Unifying Flow Matching and Energy-Based Models for Generative Modeling
Michal Balcerak, Tamaz Amiranashvili, Antonio Terpin et al.
Energy-Weighted Flow Matching for Offline Reinforcement Learning
Shiyuan Zhang, Weitong Zhang, Quanquan Gu
Fast Solvers for Discrete Diffusion Models: Theory and Applications of High-Order Algorithms
Yinuo Ren, Haoxuan Chen, Yuchen Zhu et al.
Flow matching achieves almost minimax optimal convergence
Kenji Fukumizu, Taiji Suzuki, Noboru Isobe et al.
Generator Matching: Generative modeling with arbitrary Markov processes
Peter Holderrieth, Marton Havasi, Jason Yim et al.
Go-with-the-Flow: Motion-Controllable Video Diffusion Models Using Real-Time Warped Noise
Ryan Burgert, Yuancheng Xu, Wenqi Xian et al.
High-Order Flow Matching: Unified Framework and Sharp Statistical Rates
Maojiang Su, Jerry Yao-Chieh Hu, Yi-Chen Lee et al.
Informed Correctors for Discrete Diffusion Models
Yixiu Zhao, Jiaxin Shi, Feng Chen et al.
Integrating Protein Dynamics into Structure-Based Drug Design via Full-Atom Stochastic Flows
Xiangxin Zhou, Yi Xiao, Haowei Lin et al.
LaGeM: A Large Geometry Model for 3D Representation Learning and Diffusion
Biao Zhang, Peter Wonka
MET3R: Measuring Multi-View Consistency in Generated Images
Mohammad Asim, Christopher Wewer, Thomas Wimmer et al.
MOFFlow: Flow Matching for Structure Prediction of Metal-Organic Frameworks
Nayoung Kim, Seongsu Kim, Minsu Kim et al.
Multi-Modal and Multi-Attribute Generation of Single Cells with CFGen
Alessandro Palma, Till Richter, Hanyi Zhang et al.
On the Feature Learning in Diffusion Models
Andi Han, Wei Huang, Yuan Cao et al.
Physics-Informed Diffusion Models
Jan-Hendrik Bastek, WaiChing Sun, Dennis Kochmann
Proper Hölder-Kullback Dirichlet Diffusion: A Framework for High Dimensional Generative Modeling
Wanpeng Zhang, Yuhao Fang, Xihang Qiu et al.
Riemannian Flow Matching for Brain Connectivity Matrices via Pullback Geometry
Antoine Collas, Ce Ju, Nicolas Salvy et al.
Sampling 3D Molecular Conformers with Diffusion Transformers
J. Thorben Frank, Winfried Ripken, Gregor Lied et al.
Steering Protein Family Design through Profile Bayesian Flow
Jingjing Gong, Yu Pei, Siyu Long et al.
SummDiff: Generative Modeling of Video Summarization with Diffusion
Kwanseok Kim, Jaehoon Hahm, Sumin Kim et al.
TreeGen: A Bayesian Generative Model for Hierarchies
Marcel Kollovieh, Nils Fleischmann, Filippo Guerranti et al.
Trivialized Momentum Facilitates Diffusion Generative Modeling on Lie Groups
Yuchen Zhu, Tianrong Chen, Lingkai Kong et al.
Why Masking Diffusion Works: Condition on the Jump Schedule for Improved Discrete Diffusion
Alan Amin, Nate Gruver, Andrew Wilson
Activation-Descent Regularization for Input Optimization of ReLU Networks
Hongzhan Yu, Sicun Gao
Align Your Steps: Optimizing Sampling Schedules in Diffusion Models
Amirmojtaba Sabour, Sanja Fidler, Karsten Kreis
AlphaFold Meets Flow Matching for Generating Protein Ensembles
Bowen Jing, Bonnie Berger, Tommi Jaakkola
Compositional Image Decomposition with Diffusion Models
Jocelin Su, Nan Liu, Yanbo Wang et al.
Data-free Distillation of Diffusion Models with Bootstrapping
Jiatao Gu, Chen Wang, Shuangfei Zhai et al.
Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution
Aaron Lou, Chenlin Meng, Stefano Ermon
Generative Conditional Distributions by Neural (Entropic) Optimal Transport
Bao Nguyen, Binh Nguyen, Trung Hieu Nguyen et al.
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
Jaehyeong Jo, Sung Ju Hwang
Integrating Multimodal Data for Joint Generative Modeling of Complex Dynamics
Manuel Brenner, Florian Hess, Georgia Koppe et al.
Isometric Representation Learning for Disentangled Latent Space of Diffusion Models
Jaehoon Hahm, Junho Lee, Sunghyun Kim et al.
Latent Space Editing in Transformer-Based Flow Matching
Vincent Tao Hu, Wei Zhang, Meng Tang et al.
LayoutDETR: Detection Transformer Is a Good Multimodal Layout Designer
Ning Yu, Chia-Chih Chen, Zeyuan Chen et al.
Learning Latent Space Hierarchical EBM Diffusion Models
Jiali Cui, Tian Han
Optimal Recurrent Network Topologies for Dynamical Systems Reconstruction
Christoph Jürgen Hemmer, Manuel Brenner, Florian Hess et al.
Particle Denoising Diffusion Sampler
Angus Phillips, Hai-Dang Dau, Michael Hutchinson et al.
Probabilistic Forecasting with Stochastic Interpolants and Föllmer Processes
Yifan Chen, Mark Goldstein, Mengjian Hua et al.
Protein Conformation Generation via Force-Guided SE(3) Diffusion Models
YAN WANG, Lihao Wang, Yuning Shen et al.