Training generative neural networks via Maximum Mean Discrepancy optimization

14 May 2015

Gintare Karolina Dziugaite

Papers citing "Training generative neural networks via Maximum Mean Discrepancy optimization"

50 / 125 papers shown

Title
Boosting Statistic Learning with Synthetic Data from Pretrained Large Models Jialong Jiang Wenkang Hu Jian Huang Yuling Jiao Xu Liu DiffM 50 0 0 08 May 2025
ReLU integral probability metric and its applications Yuha Park Kunwoong Kim Insung Kong Yongdai Kim 50 0 0 26 Apr 2025
A Dictionary of Closed-Form Kernel Mean Embeddings F. Briol A. Gessner Toni Karvonen Maren Mahsereci BDL 90 1 0 26 Apr 2025
High-Performance Reinforcement Learning on Spot: Optimizing Simulation Parameters with Distributional Measures A. J Miller Fangzhou Yu Michael Brauckmann Farbod Farshidian OffRL BDL 23 0 0 24 Apr 2025
Proper scoring rules for estimation and forecast evaluation Kartik Waghmare Johanna Ziegel AI4TS 35 0 0 02 Apr 2025
Audio-visual cross-modality knowledge transfer for machine learning-based in-situ monitoring in laser additive manufacturing Jiarui Xie Mutahar Safdar Lequn Chen Seung Ki Moon Y. Zhao 51 1 0 09 Aug 2024
Efficient Prior Calibration From Indirect Data O. Deniz Akyildiz Mark Girolami Andrew M. Stuart Arnaud Vadeboncoeur 44 1 0 28 May 2024
Generative adversarial learning with optimal input dimension and its adaptive generator architecture Zhiyao Tan Ling Zhou Huazhen Lin GAN 44 0 0 06 May 2024
Towards Robust Graph Incremental Learning on Evolving Graphs Junwei Su Difan Zou Zijun Zhang Chuan Wu CLL OOD 43 18 0 20 Feb 2024
DySLIM: Dynamics Stable Learning by Invariant Measure for Chaotic Systems Yair Schiff Zhong Yi Wan Jeffrey B. Parker Stephan Hoyer Volodymyr Kuleshov Fei Sha Leonardo Zepeda-Núñez 36 13 0 06 Feb 2024
Adaptive trajectory-constrained exploration strategy for deep reinforcement learning Guojian Wang Faguo Wu Xiao Zhang Ning Guo Zhiming Zheng 41 3 0 27 Dec 2023
Evading DeepFake Detectors via Adversarial Statistical Consistency Yang Hou Qing Guo Yihao Huang Xiaofei Xie Lei Ma Jianjun Zhao AAML 34 48 0 23 Apr 2023
A Semi-Bayesian Nonparametric Estimator of the Maximum Mean Discrepancy Measure: Applications in Goodness-of-Fit Testing and Generative Adversarial Networks Forough Fazeli Asl M. Zhang Lizhen Lin 29 1 0 05 Mar 2023
Differentially Private Neural Tangent Kernels for Privacy-Preserving Data Generation Yilin Yang Kamil Adamczewski Danica J. Sutherland Xiaoxiao Li Mijung Park 33 14 0 03 Mar 2023
Redes Generativas Adversarias (GAN) Fundamentos Teóricos y Aplicaciones J. D. L. Torre GAN 26 1 0 18 Feb 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 42 12 0 27 Jan 2023
Fast Inference in Denoising Diffusion Models via MMD Finetuning Emanuele Aiello D. Valsesia E. Magli DiffM 22 4 0 19 Jan 2023
Blessings and Curses of Covariate Shifts: Adversarial Learning Dynamics, Directional Convergence, and Equilibria Tengyuan Liang 22 1 0 05 Dec 2022
Proper losses for discrete generative models Rafael Frongillo Dhamma Kimpara Bo Waggoner 24 3 0 07 Nov 2022
Minimum Kernel Discrepancy Estimators Chris J. Oates 34 10 0 28 Oct 2022
Variance-Aware Estimation of Kernel Mean Embedding Geoffrey Wolfer Pierre Alquier 33 4 0 13 Oct 2022
Targeted Separation and Convergence with Kernel Discrepancies Alessandro Barp Carl-Johann Simon-Gabriel Mark Girolami Lester W. Mackey 66 14 0 26 Sep 2022
Dr. Neurosymbolic, or: How I Learned to Stop Worrying and Accept Statistics Masataro Asai 25 0 0 08 Sep 2022
Equivariant Disentangled Transformation for Domain Generalization under Combination Shift Yivan Zhang Jindong Wang Xingxu Xie Masashi Sugiyama OOD 44 1 0 03 Aug 2022
Self-supervised learning with rotation-invariant kernels Léon Zheng Gilles Puy E. Riccietti Patrick Pérez Rémi Gribonval SSL 27 2 0 28 Jul 2022
Conditional Born machine for Monte Carlo event generation Oriel Kiss Michele Grossi E. Kajomovitz S. Vallecorsa 41 14 0 16 May 2022
$α$ -GAN: Convergence and Estimation Guarantees Gowtham R. Kurri Monica Welfert Tyler Sypherd Lalitha Sankar GAN 98 8 0 12 May 2022
Geometric Methods for Sampling, Optimisation, Inference and Adaptive Agents Alessandro Barp Lancelot Da Costa G. Francca Karl J. Friston Mark Girolami Michael I. Jordan G. Pavliotis 38 25 0 20 Mar 2022
Generative Adversarial Networks Gilad Cohen Raja Giryes GAN 27 29,986 0 01 Mar 2022
Moment Matching Deep Contrastive Latent Variable Models Ethan Weinberger Nicasia Beebe-Wang Su-In Lee 31 16 0 21 Feb 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 36 42 0 09 Feb 2022
Depth and Feature Learning are Provably Beneficial for Neural Network Discriminators Carles Domingo-Enrich MLT MDE 36 0 0 27 Dec 2021
Probabilistic Forecasting with Generative Networks via Scoring Rule Minimization Lorenzo Pacchiardi Rilwan A. Adewoyin P. Dueben Ritabrata Dutta AI4TS 24 21 0 15 Dec 2021
RafterNet: Probabilistic predictions in multi-response regression Marius Hofert Avinash Prasad Mu Zhu 24 2 0 02 Dec 2021
Composite Goodness-of-fit Tests with Kernels Oscar Key Arthur Gretton F. Briol T. Fernandez 36 14 0 19 Nov 2021
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful Joeri Hermans Arnaud Delaunoy François Rozet Antoine Wehenkel Volodimir Begy Gilles Louppe 64 38 0 13 Oct 2021
F-Divergences and Cost Function Locality in Generative Modelling with Quantum Circuits Chiara Leadbeater Louis Sharrock Brian Coyle Marcello Benedetti 22 11 0 08 Oct 2021
Implicit Generative Copulas Tim Janke M. Ghanmi F. Steinke 35 17 0 29 Sep 2021
Reversible Gromov-Monge Sampler for Simulation-Based Inference Y. Hur Wenxuan Guo Tengyuan Liang 36 9 0 28 Sep 2021
Rethinking Multidimensional Discriminator Output for Generative Adversarial Networks M. Dai Haibin Hang A. Srivastava 18 3 0 08 Sep 2021
Lifelong Infinite Mixture Model Based on Knowledge-Driven Dirichlet Process Fei Ye A. Bors CLL 31 18 0 25 Aug 2021
A Pragmatic Look at Deep Imitation Learning Kai Arulkumaran D. Lillrank 35 9 0 04 Aug 2021
Dual Training of Energy-Based Models with Overparametrized Shallow Neural Networks Carles Domingo-Enrich A. Bietti Marylou Gabrié Joan Bruna Eric Vanden-Eijnden FedML 43 6 0 11 Jul 2021
Discrepancy-based Inference for Intractable Generative Models using Quasi-Monte Carlo Ziang Niu J. Meier F. Briol 39 12 0 22 Jun 2021
KALE Flow: A Relaxed KL Gradient Flow for Probabilities with Disjoint Support Pierre Glaser Michael Arbel Arthur Gretton 52 37 0 16 Jun 2021
Realizing GANs via a Tunable Loss Function Gowtham R. Kurri Tyler Sypherd Lalitha Sankar GAN 14 16 0 09 Jun 2021
Inverse design of two-dimensional materials with invertible neural networks Victor Fung Jiaxin Zhang Guoxiang Hu P. Ganesh B. Sumpter 28 41 0 06 Jun 2021
MineGAN++: Mining Generative Models for Efficient Knowledge Transfer to Limited Data Domains Yaxing Wang Abel Gonzalez-Garcia Chenshen Wu Luis Herranz Fahad Shahbaz Khan Shangling Jui Joost van de Weijer 32 6 0 28 Apr 2021
Rates of convergence for density estimation with generative adversarial networks Nikita Puchkin S. Samsonov Denis Belomestny Eric Moulines A. Naumov 37 10 0 30 Jan 2021
Applications of multivariate quasi-random sampling with neural networks Marius Hofert Avinash Prasad Mu Zhu 26 1 0 15 Dec 2020