Implicit Generative Modeling

Latest papers

8 papers2 papers in the last four weeks, with none the four weeks before. 0.0% of all new papers.

Shrinkage prior for implicit generative models
Nov 3, 2026Shreya Sinha-Roy, Christian P. Robert, Ritabrata DuttaImplicit Generative Modeling Generative Modeling
Department of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom · CEREMADE, Université Paris Dauphine PSL, France
Infinite Worlds from One Example: What Local Generators Must Share
Oct 31, 2026Amin Najafgholizadeh, Mohsen AfsharchiImplicit Generative Modeling Procedural Content Generation
Department of Computer Engineering, University of Zanjan.
Controlling Dependence in Implicit Generative Models via Spread Mutual Information
Oct 7, 2026Jiahao Yu, Song Liu, José Miguel Hernández-Lobato +1Implicit Generative Modeling Generative Modeling
University of Oxford · Work completed at the University of Cambridge. · University of Bristol +1
Renormalization Group Flow Matching for Scalable Local Generative Modeling
Aug 24, 2026Kanta Masuki, Yuto AshidaImplicit Generative Modeling Renormalization Group
Department of Physics, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan · Institute for Physics of Intelligence, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-0033, Japan
RiskFlow: Fast and Faithful Safety-Critical Traffic Scenario Generation
Jun 4, 2026Jie Li, Qi Lan, Yining Tang +5Flow Matching Implicit Generative Modeling
College of Mechanical and Vehicle Engineering Chongqing University, Chongqing, China
Synthesizing real-world distributions from high-dimensional Gaussian Noise with Fully Connected Neural Network
Apr 10, 2026Joanna KomorniczakImplicit Generative Modeling Synthetic Tabular Data Generation
Department of Systems and Computer Networks, Wrocław University of Science and Technology
Test-Time Instance-Specific Parameter Composition: A New Paradigm for Adaptive Generative Modeling
Mar 29, 2026Minh-Tuan Tran, Xuan-May Le, Quan Hung Tran +3Implicit Generative Modeling Generative Modeling
Monash University · The University of Melbourne · Meta Inc
Rethinking Diffusion Models with Symmetries through Canonicalization with Applications to Molecular Graph Generation
Feb 16, 2026Cai Zhou, Zijie Chen, Zian Li +7Implicit Generative Modeling Generative Modeling
Massachusetts Institute of Technology · Zhejiang University · Peking University +3

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Shrinkage prior for implicit generative models

Shreya Sinha-Roy, Christian P. Robert, Ritabrata Dutta

Department of Statistics, University of Warwick, Coventry, CV4 7AL, United Kingdom · CEREMADE, Université Paris Dauphine PSL, France

Implicit Generative Modeling Generative Modeling Bayesian Inference Markov Chain Monte Carlo

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Implicit generative models based on deep neural networks have revolutionized many scientific fields, from weather research to language generation. They successfully model complex random objects arising in real-world problems. In this work, we propose a sample-efficient training mechanism for these models. Our approach leverages regularized inference with shrinkage priors and generalized Bayes. In the large

p

(parameter dimension) and small

n

(sample size) setting, sparsity-inducing priors have been successfully used for linear regression when

p \gg n

. However, their application to implicit generative models remains challenging due to the intractability of the likelihood function. To address this, we adapt a scoring rule posterior based on a strictly proper scoring rule, following the generalized Bayes framework. We then propose a block SGMCMC within Gibbs sampling mechanism. This enables efficient exploration of high-dimensional parameter spaces by identifying a sparse representation of neural implicit generative models. We demonstrate the performance of our proposed method through experiments on

p \gg n

linear regression and an application of neural generative models.