Residual Flows for Invertible Generative Modeling

6 June 2019

Papers citing "Residual Flows for Invertible Generative Modeling"

50 / 106 papers shown

Title
HepatoGEN: Generating Hepatobiliary Phase MRI with Perceptual and Adversarial Models Jens Hooge Gerard Sanroma-Guell Faidra Stavropoulou Alexander Ullmann Gesine Knobloch Mark Klemens Carola Schmidt Sabine Weckbach Andreas Bolz DiffM MedIm 97 0 0 25 Apr 2025
WaterFlow: Learning Fast & Robust Watermarks using Stable Diffusion Vinay Shukla Prachee Sharma Ryan A. Rossi Sungchul Kim Tong Yu Aditya Grover WIGM 42 0 0 15 Apr 2025
Learning to Animate Images from A Few Videos to Portray Delicate Human Actions Haoxin Li Yingchen Yu Qilong Wu Hanwang Zhang Boyang Li Song Bai 3DH VGen 242 0 0 01 Mar 2025
Model Synthesis for Zero-Shot Model Attribution Tianyun Yang Juan Cao Danding Wang Chang Xu WIGM 86 4 0 20 Jan 2025
Generative Modelling with High-Order Langevin Dynamics Ziqiang Shi Rujie Liu DiffM 64 2 0 03 Jan 2025
vMF-Contact: Uncertainty-aware Evidential Learning for Probabilistic Contact-grasp in Noisy Clutter Yitian Shi Edgar Welte Maximilian Gilles Rania Rayyes 43 3 0 06 Nov 2024
Gradients of Functions of Large Matrices Nicholas Krämer Pablo Moreno-Muñoz Hrittik Roy Søren Hauberg 40 0 0 27 May 2024
Learning Stable and Passive Neural Differential Equations Jing Cheng Ruigang Wang I. Manchester 34 3 0 19 Apr 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 59 6 0 08 Apr 2024
Generative AI and Process Systems Engineering: The Next Frontier Benjamin Decardi-Nelson Abdulelah S. Alshehri Akshay Ajagekar Fengqi You AI4CE LLMAG 37 24 0 15 Feb 2024
Classification Diffusion Models: Revitalizing Density Ratio Estimation Shahar Yadin Noam Elata T. Michaeli DiffM 48 1 0 15 Feb 2024
Monotone, Bi-Lipschitz, and Polyak-Lojasiewicz Networks Ruigang Wang Krishnamurthy Dvijotham I. Manchester 41 5 0 02 Feb 2024
How Smooth Is Attention? Valérie Castin Pierre Ablin Gabriel Peyré AAML 40 9 0 22 Dec 2023
ACT-Diffusion: Efficient Adversarial Consistency Training for One-step Diffusion Models Fei Kong Jinhao Duan Lichao Sun Hao-Ran Cheng Renjing Xu Hengtao Shen Xiao-lan Zhu Xiaoshuang Shi Kaidi Xu 44 3 0 23 Nov 2023
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning Amey P. Pasarkar Adji Bousso Dieng 34 11 0 19 Oct 2023
Diffusion Models with Deterministic Normalizing Flow Priors Mohsen Zand Ali Etemad Michael A. Greenspan DiffM 34 2 0 03 Sep 2023
Computing excited states of molecules using normalizing flows Yahya Saleh Álvaro Fernández Corral Emil Vogt Armin Iske J. Küpper A. Yachmenev 38 7 0 31 Aug 2023
A Review of Change of Variable Formulas for Generative Modeling Ullrich Kothe 34 6 0 04 Aug 2023
Complementary Frequency-Varying Awareness Network for Open-Set Fine-Grained Image Recognition Qiulei Dong Hong Wang Qiulei Dong 30 0 0 14 Jul 2023
Lifting Architectural Constraints of Injective Flows Peter Sorrenson Felix Dräxler Armand Rousselot Sander Hummerich Leandro Zimmerman Ullrich Kothe TPM AI4CE 39 8 0 02 Jun 2023
On the Generalization and Approximation Capacities of Neural Controlled Differential Equations Linus Bleistein Agathe Guilloux 40 1 0 26 May 2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives Chen-Hao Chao Wei-Fang Sun Yen-Chang Hsu Z. Kira Chun-Yi Lee 33 3 0 24 May 2023
Enhancing Multiple Reliability Measures via Nuisance-extended Information Bottleneck Jongheon Jeong Sihyun Yu Hankook Lee Jinwoo Shin AAML 49 0 0 24 Mar 2023
PITS: Variational Pitch Inference without Fundamental Frequency for End-to-End Pitch-controllable TTS Junhyeok Lee Wonbin Jung Hyunjae Cho Jaeyeon Kim Jaehwan Kim 22 3 0 24 Feb 2023
Star-Shaped Denoising Diffusion Probabilistic Models Andrey Okhotin Dmitry Molchanov V. Arkhipkin Grigory Bartosh Viktor Ohanesian Aibek Alanov Dmitry Vetrov DiffM 45 12 0 10 Feb 2023
Learning Data Representations with Joint Diffusion Models Kamil Deja Tomasz Trzciñski Jakub M. Tomczak DiffM 30 15 0 31 Jan 2023
Certified Invertibility in Neural Networks via Mixed-Integer Programming Tianqi Cui Tom S. Bertalan George J. Pappas M. Morari Ioannis G. Kevrekidis Mahyar Fazlyab AAML 27 2 0 27 Jan 2023
EndoBoost: a plug-and-play module for false positive suppression during computer-aided polyp detection in real-world colonoscopy (with dataset) Haoran Wang Yan Zhu W. Qin Yizhe Zhang Pinghong Zhou Quanlin Li Shuo Wang Zhijian Song 34 2 0 23 Dec 2022
Denoising Deep Generative Models G. Loaiza-Ganem Brendan Leigh Ross Luhuan Wu John P. Cunningham Jesse C. Cresswell Anthony L. Caterini DiffM 36 5 0 30 Nov 2022
Proximal Residual Flows for Bayesian Inverse Problems J. Hertrich BDL TPM 44 4 0 30 Nov 2022
Normalizing Flow with Variational Latent Representation Hanze Dong Shizhe Diao Weizhong Zhang Tong Zhang BDL OOD DRL 16 0 0 21 Nov 2022
Spectral Regularization: an Inductive Bias for Sequence Modeling Kaiwen Hou Guillaume Rabusseau 16 3 0 04 Nov 2022
Invertible Rescaling Network and Its Extensions Mingqing Xiao Shuxin Zheng Chang-Shu Liu Zhouchen Lin Tie-Yan Liu 37 27 0 09 Oct 2022
Flow Matching for Generative Modeling Y. Lipman Ricky T. Q. Chen Heli Ben-Hamu Maximilian Nickel Matt Le OOD 63 1,081 0 06 Oct 2022
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models Chen Liang Wenguan Wang Jiaxu Miao Yi Yang VLM 46 117 0 05 Oct 2022
Neural Conservation Laws: A Divergence-Free Perspective Jack Richter-Powell Y. Lipman Ricky T. Q. Chen 56 51 0 04 Oct 2022
Neural PCA for Flow-Based Representation Learning Shen Li Bryan Hooi DRL 13 1 0 23 Aug 2022
Verifying the Union of Manifolds Hypothesis for Image Data Bradley Brown Anthony L. Caterini Brendan Leigh Ross Jesse C. Cresswell G. Loaiza-Ganem 44 39 0 06 Jul 2022
A Flexible Diffusion Model Weitao Du Tao Yang Heidi Zhang Yuanqi Du DiffM 38 11 0 17 Jun 2022
Entangled Residual Mappings Mathias Lechner Ramin Hasani Z. Babaiee Radu Grosu Daniela Rus T. Henzinger Sepp Hochreiter 16 5 0 02 Jun 2022
Invertible Neural Networks for Graph Prediction Chen Xu Xiuyuan Cheng Yao Xie GNN 31 9 0 02 Jun 2022
Flowification: Everything is a Normalizing Flow Bálint Máté Samuel Klein T. Golling Franccois Fleuret 28 3 0 30 May 2022
Maximum Likelihood Training of Implicit Nonlinear Diffusion Models Dongjun Kim Byeonghu Na S. Kwon Dongsoo Lee Wanmo Kang Il-Chul Moon DiffM 213 52 0 27 May 2022
A Tale of Two Flows: Cooperative Learning of Langevin Flow and Normalizing Flow Toward Energy-Based Model Jianwen Xie Y. Zhu Juntao Li Ping Li 29 50 0 13 May 2022
SIReN-VAE: Leveraging Flows and Amortized Inference for Bayesian Networks Jacobie Mouton Steve Kroon DRL BDL 26 0 0 23 Apr 2022
FastFlows: Flow-Based Models for Molecular Graph Generation Nathan C. Frey V. Gadepally Bharath Ramsundar 36 12 0 28 Jan 2022
WPPNets and WPPFlows: The Power of Wasserstein Patch Priors for Superresolution Fabian Altekrüger J. Hertrich 32 15 0 20 Jan 2022
$$m^\ast$ of two-dimensional electron gas: a neural canonical transformation study$ $m^\ast$ of two-dimensional electron gas: a neural canonical transformation study H.-j. Xie Linfeng Zhang Lei Wang 36 8 0 10 Jan 2022
A Compact Neural Network-based Algorithm for Robust Image Watermarking Hongcai Xu Rong Wang Jia Wei Shao-Ping Lu 29 13 0 27 Dec 2021
Score-Based Generative Modeling with Critically-Damped Langevin Diffusion Tim Dockhorn Arash Vahdat Karsten Kreis DiffM 32 231 0 14 Dec 2021