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Variational Inference with Normalizing Flows

21 May 2015

Danilo Jimenez Rezende

Papers citing "Variational Inference with Normalizing Flows"

50 / 2,268 papers shown

Title
TEA: Test-time Energy Adaptation Yige Yuan Bingbing Xu Liang Hou Fei Sun Huawei Shen Xueqi Cheng TTA VLM 85 11 0 24 Nov 2023
On diffusion-based generative models and their error bounds: The log-concave case with full convergence estimates Stefano Bruno Ying Zhang Dong-Young Lim Ömer Deniz Akyildiz Sotirios Sabanis DiffM 110 5 0 22 Nov 2023
Using Human Feedback to Fine-tune Diffusion Models without Any Reward Model Kai Yang Jian Tao Jiafei Lyu Chunjiang Ge Jiaxin Chen Qimai Li Weihan Shen Xiaolong Zhu Xiu Li EGVM 129 109 0 22 Nov 2023
Variational Elliptical Processes Maria B˙ankestad Jens Sjölund Jalil Taghia Thomas B. Schon 87 2 0 21 Nov 2023
FrePolad: Frequency-Rectified Point Latent Diffusion for Point Cloud Generation Chenliang Zhou Fangcheng Zhong Param Hanji Zhilin Guo Kyle Fogarty Alejandro Sztrajman Hongyun Gao Cengiz Öztireli 80 3 0 20 Nov 2023
Gaussian Interpolation Flows Yuan Gao Jianxia Huang Yuling Jiao AI4CE 81 3 0 20 Nov 2023
A Survey of Emerging Applications of Diffusion Probabilistic Models in MRI Yuheng Fan Hanxi Liao Shiqi Huang Yimin Luo Huazhu Fu Haikun Qi MedIm 98 21 0 19 Nov 2023
Direct Amortized Likelihood Ratio Estimation Adam D. Cobb Brian Matejek Daniel Elenius Anirban Roy Susmit Jha 54 2 0 17 Nov 2023
DIFFNAT: Improving Diffusion Image Quality Using Natural Image Statistics Aniket Roy Maiterya Suin Anshul B. Shah Ketul Shah Jiang-Long Liu Rama Chellappa DiffM 83 4 0 16 Nov 2023
On the Quantification of Image Reconstruction Uncertainty without Training Data Sirui Bi Victor Fung Jiaxin Zhang 55 1 0 16 Nov 2023
Are Normalizing Flows the Key to Unlocking the Exponential Mechanism? Robert A. Bridges Vandy J. Tombs Christopher B. Stanley 51 1 0 15 Nov 2023
Uncertainty Estimation on Sequential Labeling via Uncertainty Transmission Jianfeng He Linlin Yu Shuo Lei Chang-Tien Lu Feng Chen UQLM 55 10 0 15 Nov 2023
arfpy: A python package for density estimation and generative modeling with adversarial random forests Kristin Blesch Marvin N. Wright 57 2 0 13 Nov 2023
Simplifying Complex Observation Models in Continuous POMDP Planning with Probabilistic Guarantees and Practice Idan Lev-Yehudi Moran Barenboim Vadim Indelman 144 6 0 13 Nov 2023
CL-Flow:Strengthening the Normalizing Flows by Contrastive Learning for Better Anomaly Detection Shunfeng Wang Yueyang Li Haichi Luo Chenyang Bi 73 1 0 12 Nov 2023
TURBO: The Swiss Knife of Auto-Encoders Guillaume Quétant Yury Belousov Vitaliy Kinakh Svyatoslav Voloshynovskiy 58 6 0 11 Nov 2023
EVORA: Deep Evidential Traversability Learning for Risk-Aware Off-Road Autonomy Xiaoyi Cai Siddharth Ancha Lakshay Sharma Philip R. Osteen Bernadette Bucher Stephen Phillips Jiuguang Wang Michael Everett Nicholas Roy Jonathan P. How EDL 92 36 0 10 Nov 2023
Improvements on Uncertainty Quantification for Node Classification via Distance-Based Regularization Russell Hart Linlin Yu Yifei Lou Feng Chen UQCV 64 4 0 10 Nov 2023
Conditional Optimal Transport on Function Spaces Bamdad Hosseini Alexander W. Hsu Amirhossein Taghvaei OT 122 16 0 09 Nov 2023
Retinal OCT Synthesis with Denoising Diffusion Probabilistic Models for Layer Segmentation Yuli Wu Weidong He Dennis Eschweiler Ningxin Dou Zixin Fan Shengli Mi Peter Walter Johannes Stegmaier MedIm DiffM 87 3 0 09 Nov 2023
The voraus-AD Dataset for Anomaly Detection in Robot Applications Jan Thiess Brockmann Marco Rudolph Bodo Rosenhahn Bastian Wandt 74 11 0 08 Nov 2023
Weakly-supervised deepfake localization in diffusion-generated images Dragos Tantaru Elisabeta Oneata Dan Oneaţă DiffM 70 25 0 08 Nov 2023
Improved DDIM Sampling with Moment Matching Gaussian Mixtures Prasad Gabbur DiffM 50 1 0 08 Nov 2023
Structured Neural Networks for Density Estimation and Causal Inference Asic Q. Chen Ruian Shi Xiang Gao Ricardo Baptista Rahul G. Krishnan CML TPM 84 7 0 03 Nov 2023
Monotone Generative Modeling via a Gromov-Monge Embedding Wonjun Lee Yifei Yang Dongmian Zou Gilad Lerman GAN 99 2 0 02 Nov 2023
LLM4Drive: A Survey of Large Language Models for Autonomous Driving Zhenjie Yang Xiaosong Jia Hongyang Li Junchi Yan ELM 142 122 0 02 Nov 2023
A Review and Roadmap of Deep Causal Model from Different Causal Structures and Representations Hang Chen Keqing Du Chenguang Li Xinyu Yang 104 2 0 02 Nov 2023
Minimizing Convex Functionals over Space of Probability Measures via KL Divergence Gradient Flow Rentian Yao Linjun Huang Yun Yang 92 4 0 01 Nov 2023
Rethinking Variational Inference for Probabilistic Programs with Stochastic Support Tim Reichelt C. Ong Tom Rainforth 68 2 0 01 Nov 2023
Boosting Summarization with Normalizing Flows and Aggressive Training Yu Yang Xiaotong Shen AI4CE TPM 78 0 0 01 Nov 2023
Polynomial Chaos Surrogate Construction for Random Fields with Parametric Uncertainty Joy N. Mueller K. Sargsyan Craig J. Daniels H. Najm 47 0 0 01 Nov 2023
Diffusion models for probabilistic programming Simon Dirmeier Fernando Pérez-Cruz 81 1 0 01 Nov 2023
Uncertainty quantification and out-of-distribution detection using surjective normalizing flows Simon Dirmeier Ye Hong Yanan Xin Fernando Pérez-Cruz UQCV 67 1 0 01 Nov 2023
The Missing U for Efficient Diffusion Models Sergio Calvo-Ordoñez Chun-Wun Cheng Jiahao Huang Lipei Zhang Guang Yang Carola-Bibiane Schonlieb Angelica I Aviles-Rivero DiffM 104 4 0 31 Oct 2023
The SVHN Dataset Is Deceptive for Probabilistic Generative Models Due to a Distribution Mismatch Tim Z. Xiao Johannes Zenn Robert Bamler 36 0 0 30 Oct 2023
Rare Event Probability Learning by Normalizing Flows Zhenggqi Gao Dinghuai Zhang Luca Daniel Duane S. Boning 75 3 0 29 Oct 2023
Knowledge-based in silico models and dataset for the comparative evaluation of mammography AI for a range of breast characteristics, lesion conspicuities and doses E. Sizikova Niloufar Saharkhiz D. Sharma Miguel Lago B. Sahiner Jana G. Delfino Aldo Badano 59 6 0 27 Oct 2023
Deep Transformed Gaussian Processes Francisco Javier Sáez-Maldonado Juan Maroñas Daniel Hernández-Lobato 95 0 0 27 Oct 2023
Improving Denoising Diffusion Models via Simultaneous Estimation of Image and Noise Zhenkai Zhang Krista A. Ehinger Tom Drummond DiffM 62 0 0 26 Oct 2023
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration Longlin Yu Tianyu Xie Yu Zhu Tong Yang Xiangyu Zhang Cheng Zhang DiffM 66 10 0 26 Oct 2023
Reimagining Synthetic Tabular Data Generation through Data-Centric AI: A Comprehensive Benchmark Lasse Hansen Nabeel Seedat M. Schaar Andrija Petrović 134 21 0 25 Oct 2023
Posterior Consistency for Missing Data in Variational Autoencoders Timur Sudak Sebastian Tschiatschek 42 3 0 25 Oct 2023
Free-form Flows: Make Any Architecture a Normalizing Flow Felix Dräxler Peter Sorrenson Lea Zimmermann Armand Rousselot Ullrich Kothe TPM DRL AI4CE BDL 103 11 0 25 Oct 2023
Learning Low-Rank Latent Spaces with Simple Deterministic Autoencoder: Theoretical and Empirical Insights Alokendu Mazumder Tirthajit Baruah Bhartendu Kumar Rishab Sharma Vishwajeet Pattanaik Punit Rathore 31 1 0 24 Oct 2023
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation Yanfang Liu Minglei Yang Zezhong Zhang Feng Bao Yanzhao Cao Guannan Zhang 62 16 0 22 Oct 2023
Normalizing flow-based deep variational Bayesian network for seismic multi-hazards and impacts estimation from InSAR imagery Xuechun Li Paula M. Burgi Wei Ma Hae Young Noh David J. Wald Susu Xu 26 3 0 20 Oct 2023
Generative Marginalization Models Sulin Liu Peter J. Ramadge Ryan P. Adams 74 1 0 19 Oct 2023
Canonical normalizing flows for manifold learning Kyriakos Flouris E. Konukoglu DRL 121 9 0 19 Oct 2023
Learning to Sample Better M. S. Albergo Eric Vanden-Eijnden BDL 39 1 0 17 Oct 2023
Probabilistic Classification by Density Estimation Using Gaussian Mixture Model and Masked Autoregressive Flow Benyamin Ghojogh Milad Amir Toutounchian 47 0 0 16 Oct 2023