Generative Modeling

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39 papers in the last four weeks, up 144% on the four weeks before. 0.4% of all new papers.

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Latest papers 347

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FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model
Sep 28, 2026Shucheng Liu, Changchun Shi, Kai Zhang +1Neural Surrogate Modeling Functional Connectivity
University of North Carolina at Chapel Hill · London School of Economics and Political Science
Scaling Versatile 3D Assets Editing with a Million-Scale Dataset
Sep 28, 2026Badi Li, Tianxin Huang, Yu Zhou +33D Asset Generation Generative Modeling
The University of Hong Kong · Shenzhen Loop Area Institute · Sun Yat-Sen University +1
JIVE: Jacobian-Informed Volume Expansion for Diverse Generative Sampling
Sep 27, 2026Guangxun Zhang, Brian Cai, Boxuan Zhang +2Generative Modeling
New York University · Stony Brook University · Rutgers University
Source Anchoring for Physical Consistency in Flow Matching Models
Sep 27, 2026Giulia Romoli, Filippo Ruffini, Paolo SodaConstrained Generative Modeling Physics-Informed Generative Modeling
Department of Diagnostics and Intervention, Ume˚a University, Sweden · Unit of Artificial Intelligence and Computer Systems, Universit`a Campus Bio-Medico di Roma, Italy
KoopCell: Koopman-Based Generative Model for Learning Single-Cell Dynamics from Distribution Snapshots
Sep 27, 2026Wanfeng Lu, Yutong Zhang, Keyi Zhou +3Koopman Operator Learning Latent Dynamics Modeling
School of Mathematical Sciences, SCMS, SCAM, and CCSB, Fudan University, China · Research Institute of Intelligent Complex Systems, Fudan University, China · State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Institutes of Brain Science, Fudan University, China +1
Topology-Stratified Materials Discovery with A Flow-Based Generative Model
Sep 22, 2026Jingyi Zhou, Oyshee Chowdhury, Noah Oyeniran +1Materials Science Generative Modeling
Department of Aerospace Engineering and Mechanics, University of Alabama, Tuscaloosa, 35487, Alabama, United States. · Alabama Materials Institute, The University of Alabama, Tuscaloosa, 35487, Alabama, United States.
Deep Generative Crystal Structure Prediction: A Benchmark Study and a Controlled Test of Prototype Dependence
Sep 22, 2026Lai Wei, Rongzhi Dong, Ying Feng +2Crystal Structure Prediction Generative Modeling
Department of Computer Science and Engineering University of South Carolina Columbia, SC 29201 · Department of Computer Science and Cybersecurity, University of North Georgia, Dahlonega, GA 30597
Bridge of $Ψ$ 's: Quantum Circuit Optimization with Schrödinger Bridges
Sep 22, 2026Lino S. Hofstetter, Lia Yeh, Prakash MuraliQuantum Circuit Compilation Generative Modeling
ETH Zürich Zürich, Switzerland · University of Cambridge Cambridge, United Kingdom
When Riemann flows with Wasserstein: Generative Modeling of Probability Distributions on Manifolds
Sep 22, 2026Doron Haviv, Edward De Brouwer, Rishabh Anand +4Riemannian Flow Matching Generative Modeling
Genentech Inc., South San Francisco, CA. · Yale University, New Haven, CT.
Empirical Auditing of Edge-Private Graph Generators
Sep 21, 2026Anum Fatima, Stratis Limnios, James Adams +4Privacy Auditing Edge Inference
Department of Statistics University of Oxford Oxford, United Kingdom · Plenitude Consulting, London, United Kingdom · National Physical Laboratory Teddington, United Kingdom +3
A discrete generative model of neuronal spiking activity on microelectrode arrays
Sep 20, 2026Md Sayed Tanveer, Mohammed A. Mostajo-Radji, Ge WangGenerative Modeling
Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA · Center for Biotechnology and Interdisciplinary Studies, Rensselaer Polytechnic Institute · Genomics Institute, University of California Santa Cruz, Santa Cruz, CA 95064, USA
SewFusion: Tailored Generation of Topology and Panel-Level Geometry for Sewing Patterns
Sep 20, 2026Jiaxin Lin, Xiao Pan, Hangjie Yuan +3Generative Modeling Autoregressive Generation
Digital Creative Technology Laboratory, Shenzhen University · Zhejiang University
Stable Filters for Generative Modeling of Graph Signals
Sep 16, 2026Martin Schmidt, Gonzalo MateosGraph Signal Processing Algorithmic Stability
University of Rochester, Rochester, NY, USA
When Edit Flows are Edit Jumps: replicating Edit Flows and EvoFlows
Sep 16, 2026Gabriel Bénédict, Melanie Buechler, Gerard Riera-Solà +3Generative Modeling Protein Design
Visium, Switzerland
Walking the Score Manifold: Continuous-time Generative Dynamics on Learned Data Manifolds
Sep 15, 2026Jan Tauberschmidt, Brian B. Moser, Stanislav Frolov +3Dynamical Systems Latent Dynamics Modeling
DFKI Kaiserslautern · RPTU Kaiserslautern · Imperial College London
From Manual Construction to AI-Driven Scenario Emergence: Rethinking Catastrophe Risk Modeling
Sep 15, 2026Hang GaoGenerative Modeling
Convergence rates for generative drifting flows: fixed-scale obstructions and multihead acceleration
Sep 14, 2026Arthur Stéphanovitch, Eddie AamariOne-Step Generative Modeling Generative Modeling
Centre de recherche en économie et statistique · ENSAE, IP Paris · Département de Mathématiques et Applications +1
Branched Optimal Transport Amortization
Sep 14, 2026Semyon Semenov, Viktor Kovalchuk, Meir Roketlishvili +4Flow Matching Generative Modeling
MBZUAI
Fast BIB simulation at a future Muon Collider with generative machine learning
Sep 14, 2026Radha Mastandrea, Shiyu Peng, Benjamin Rosser +1Tabular Diffusion Models Generative Modeling
Enrico Fermi Institute, The University of Chicago, Chicago, IL 60637, USA · Data Science Institute, The University of Chicago, Chicago, IL 60637, USA · Department of Physics, Brown University, Providence, RI 02912, USA +1
CyFM: Cylindrical Optimal Transport for Few-Step Complex-Valued Flow Matching
Sep 12, 2026Marcel Musiałek, Iga Wolanin, Damian Ryczko +2Flow Matching One-Step Generative Modeling
Wrocław University of Science and Technology Wrocław, Poland
Particle GFlowNets: Rethinking Generative Marginalization Models
Sep 11, 2026Tiago da Silva, Diego Mesquita, Salem LahlouMarkov Chain Monte Carlo Generative Flow Networks
MBZUAI · School of Applied Mathematics, Getulio Vargas Foundation
SimpleDesign: A Joint Model for Protein Sequence and Structure Codesign
Sep 3, 2026Jiarui Lu, Yuyang Wang, Yizhe Zhang +4Unified Multimodal Models Generative Modeling
Mila, Université de Montréal, Apple · Apple
Thinking in Pictures: A Systematic Benchmark for Reasoning-driven Image Generation
Sep 2, 2026Yutong Liu, Nan Huang, Xu Cao +1Image Generation Image Generation Evaluation
University of Illinois Urbana-Champaign · New York University
Full-Model Optimality for Tunable Linear Generative Priors in Compressed Sensing
Sep 2, 2026Zhaoming Li, Paul HandCompressed Sensing Model Selection
Department of Mathematics, Northeastern University, Boston, MA 02115, USA. · Department of Mathematics and Khoury College of Computer Sciences, Northeastern University, Boston, MA 02115, USA.
Do Large Language Models Capture the Diversity in their Training Data?
Sep 2, 2026Youqi Wu, Farzan FarniaGenerative Modeling
Department of Computer Science and Engineering, The Chinese University of Hong Kong
Schrödinger Bridges on Lie Group Manifolds for Probabilistic Intrinsic Generation
Sep 2, 2026Shizhe Zhang, Mingyang Zhao, Lei MaSchrödinger Bridges Generative Modeling
1National Biomedical Imaging Center, College of Future Technology, Peking University, Beijing, China · 2State Key Laboratory of Mathematical Sciences, Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing, China
A Network Science Perspective on Evaluating Deep Graph Generative Models
Sep 1, 2026Tianrui Mao, Abele Malan, Megha Khosla +2Synthetic Data Generation Generative Modeling
Delft University of Technology, the Netherlands · University of Neuchâtel, Switzerland
Motion-Saliency Complementary Masked Modeling for Point Cloud Video Understanding
Aug 31, 2026Wei Wang, Yiding Sun, Yuyan Wang +4Point Cloud Learning Generative Modeling
School of Computer Science and Technology, Xi’an Jiaotong University, Xi’an, 710049, China · Guangdong Laboratory of Artificial Intelligence and Digital Economy (SZ), Shenzhen, 518107, China · School of Software Engineering, Xi’an Jiaotong University, Xi’an, 710049, China +4
Novel Knowledge-Guided Generative Methods for Synthetic Transcriptomic Data
Aug 13, 2026Francesca Pia Panaccione, Sofia Mongardi, Marco Masseroli +1Graph Neural Networks Synthetic Data Generation
DEIB - Dipartimento Elettronica, Informazione e Bioingegneria, Politecnico di Milano, Milan, Italy
GeoCache: Training-Free Acceleration of Multi-View Texture Diffusion via Geometric Delta Transport
Aug 13, 2026Haotang Li, Zhenyu Qi, Shaohan Henry Wang +6Multi-View Consistency Generative Modeling
Department of Eletrical and Computer Engineering, University of Arizona, Tucson, AZ · Department of Computer Science, East Carolina University, Greenville, NC · Department of Computer Engineering and Computer Science,California State University, Long Beach, CA +1

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FAST-Brain: A Flow-Aligned Spatio-Temporal Surrogate Brain Model

Shucheng Liu, Changchun Shi, Kai Zhang, Hongtu Zhu

University of North Carolina at Chapel Hill · London School of Economics and Political Science

Neural Surrogate Modeling Functional Connectivity Generative Modeling Flow-Based Generative Modeling Neuroimaging Spatiotemporal GNNs+1

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Modeling resting-state functional magnetic resonance imaging (rs-fMRI) data is crucial for understanding brain-wide neural activity. However, traditional methods struggle to capture complex temporal dynamics over long horizons, to account for the brain's anatomical spatial structure, and to model high-dimensional ambient signals that lie on a low-dimensional intrinsic subspace. We propose FAST-Brain, a unified flow-aligned spatio-temporal surrogate brain model that addresses all three challenges. At its core is a flow-aligned generative framework that directly predicts the clean blood-oxygen-level-dependent (BOLD) signal, paired with a graph convolutional network that captures spatial structural constraints and a Transformer that models long-range temporal dependencies. Theoretically, we show that under a low-dimensional subspace assumption, the approximation error of our model scales with the intrinsic dimension rather than the ambient dimension, which justifies our direct modeling of the BOLD signal. Extensive experiments on synthetic and Human Connectome Project datasets demonstrate that FAST-Brain achieves state-of-the-art performance in recovering functional connectivity, effective connectivity, and the implicit low-dimensional signal subspace.

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Latest papers 347