Advances in Variational Inference

15 November 2017

Papers citing "Advances in Variational Inference"

50 / 72 papers shown

Title
Generative Modeling of Class Probability for Multi-Modal Representation Learning Jungkyoo Shin Bumsoo Kim Eunwoo Kim 50 1 0 21 Mar 2025
Bayesian Computation in Deep Learning Wenlong Chen Bolian Li Ruqi Zhang Yingzhen Li BDL 70 0 0 25 Feb 2025
Functional Complexity-adaptive Temporal Tensor Decomposition Panqi Chen Lei Cheng J. Li Weichang Li W. Liu Jiang Bian Shikai Fang CML 72 0 0 10 Feb 2025
A Robust Adversarial Ensemble with Causal (Feature Interaction) Interpretations for Image Classification Chunheng Zhao P. Pisu G. Comert N. Begashaw Varghese Vaidyan Nina Christine Hubig AAML 24 0 0 31 Dec 2024
Streamlining Prediction in Bayesian Deep Learning Rui Li Marcus Klasson Arno Solin Martin Trapp UQCV BDL 91 1 0 27 Nov 2024
Hierarchical mixtures of Unigram models for short text clustering: The role of Beta-Liouville priors Massimo Bilancia Samuele Magro 33 0 0 29 Oct 2024
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling Alex Glyn-Davies A. Vadeboncoeur O. Deniz Akyildiz Ieva Kazlauskaite Mark Girolami PINN 58 0 0 10 Sep 2024
Relaxed Quantile Regression: Prediction Intervals for Asymmetric Noise T. Pouplin Alan Jeffares Nabeel Seedat Mihaela van der Schaar 48 3 0 05 Jun 2024
Rényi Neural Processes Xuesong Wang He Zhao Edwin V. Bonilla UQCV BDL 32 0 0 25 May 2024
Analytical Approximation of the ELBO Gradient in the Context of the Clutter Problem Roumen Nikolaev Popov 19 0 0 16 Apr 2024
Stable Training of Normalizing Flows for High-dimensional Variational Inference Daniel Andrade BDL TPM 24 1 0 26 Feb 2024
Provably Scalable Black-Box Variational Inference with Structured Variational Families Joohwan Ko Kyurae Kim W. Kim Jacob R. Gardner BDL 25 1 0 19 Jan 2024
Wasserstein Gradient Flow over Variational Parameter Space for Variational Inference Dai Hai Nguyen Tetsuya Sakurai Hiroshi Mamitsuka 38 0 0 25 Oct 2023
Group Spike and Slab Variational Bayes M. Komodromos Marina Evangelou Sarah Filippi Kolyan Ray 20 2 0 19 Sep 2023
Distributed Variational Inference for Online Supervised Learning P. Paritosh Nikolay A. Atanasov Sonia Martinez 24 1 0 05 Sep 2023
Provable convergence guarantees for black-box variational inference Justin Domke Guillaume Garrigos Robert Mansel Gower 18 18 0 04 Jun 2023
Is novelty predictable? Clara Fannjiang Jennifer Listgarten AI4CE 10 14 0 01 Jun 2023
Learning Sparsity of Representations with Discrete Latent Variables Zhao Xu Daniel Oñoro-Rubio G. Serra Mathias Niepert 10 0 0 03 Apr 2023
VI-DGP: A variational inference method with deep generative prior for solving high-dimensional inverse problems Yingzhi Xia Qifeng Liao Jinglai Li 11 2 0 22 Feb 2023
Bayesian Federated Inference for estimating Statistical Models based on Non-shared Multicenter Data sets Marianne A Jonker H. Pazira Anthony C. C. Coolen FedML 10 5 0 15 Feb 2023
Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference Amine M. Remita Golrokh Vitae Abdoulaye Baniré Diallo BDL 13 0 0 06 Feb 2023
Machine Learning with High-Cardinality Categorical Features in Actuarial Applications Benjamin Avanzi G. Taylor Melantha Wang Bernard Wong 17 11 0 30 Jan 2023
Projective Integral Updates for High-Dimensional Variational Inference J. Duersch 13 1 0 20 Jan 2023
Variational Inference for Semiparametric Bayesian Novelty Detection in Large Datasets L. Benedetti Eric Boniardi Leonardo Chiani Jacopo Ghirri Marta Mastropietro A. Cappozzo Francesco Denti 19 0 0 04 Dec 2022
Offline Reinforcement Learning with Adaptive Behavior Regularization Yunfan Zhou Xijun Li Qingyu Qu OffRL 6 1 0 15 Nov 2022
Clinically Plausible Pathology-Anatomy Disentanglement in Patient Brain MRI with Structured Variational Priors Anjun Hu J. Falet Brennan Nichyporuk Changjian Shui Douglas L. Arnold Sotirios A. Tsaftaris Tal Arbel 6 2 0 15 Nov 2022
Regularized Rényi divergence minimization through Bregman proximal gradient algorithms Thomas Guilmeau Émilie Chouzenoux Victor Elvira 19 3 0 09 Nov 2022
Interactive inference: a multi-agent model of cooperative joint actions D. Maisto Francesco Donnarumma G. Pezzulo 14 15 0 24 Oct 2022
Posterior Regularized Bayesian Neural Network Incorporating Soft and Hard Knowledge Constraints Jiayu Huang Yutian Pang Yongming Liu Hao Yan BDL UQCV 9 15 0 16 Oct 2022
GFlowNets and variational inference Nikolay Malkin Salem Lahlou T. Deleu Xu Ji J. E. Hu Katie Everett Dinghuai Zhang Yoshua Bengio BDL 132 77 0 02 Oct 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 24 20 0 15 Sep 2022
MPPI-IPDDP: Hybrid Method of Collision-Free Smooth Trajectory Generation for Autonomous Robots Mingeuk Kim Kwang-Ki K. Kim 24 3 0 04 Aug 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 20 15 0 01 Aug 2022
Variational Deep Image Restoration Jae Woong Soh N. Cho SupR 38 39 0 03 Jul 2022
Rethinking Bayesian Learning for Data Analysis: The Art of Prior and Inference in Sparsity-Aware Modeling Lei Cheng Feng Yin Sergios Theodoridis S. Chatzis Tsung-Hui Chang 60 73 0 28 May 2022
Variational Kalman Filtering with Hinf-Based Correction for Robust Bayesian Learning in High Dimensions Niladri Das J. Duersch Thomas A. Catanach 10 0 0 27 Apr 2022
Guaranteed Bounds for Posterior Inference in Universal Probabilistic Programming Raven Beutner Luke Ong Fabian Zaiser 14 11 0 06 Apr 2022
Hybrid Predictive Coding: Inferring, Fast and Slow Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley 16 36 0 05 Apr 2022
Theoretical Connection between Locally Linear Embedding, Factor Analysis, and Probabilistic PCA Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley 8 3 0 25 Mar 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 10 25 0 20 Mar 2022
Diffusion Probabilistic Modeling for Video Generation Ruihan Yang Prakhar Srivastava Stephan Mandt DiffM VGen 27 255 0 16 Mar 2022
Partitioned Variational Inference: A Framework for Probabilistic Federated Learning Matthew Ashman T. Bui Cuong V Nguyen Efstratios Markou Adrian Weller S. Swaroop Richard E. Turner FedML 15 12 0 24 Feb 2022
SAFER: Data-Efficient and Safe Reinforcement Learning via Skill Acquisition Dylan Slack Yinlam Chow Bo Dai Nevan Wichers OffRL 13 7 0 10 Feb 2022
Bayesian Nonlinear Models for Repeated Measurement Data: An Overview, Implementation, and Applications Se Yoon Lee 8 17 0 28 Jan 2022
Reactive Message Passing for Scalable Bayesian Inference Dmitry V. Bagaev Bert De Vries 17 18 0 25 Dec 2021
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 27 25 0 20 Dec 2021
OnSlicing: Online End-to-End Network Slicing with Reinforcement Learning Qiang Liu Nakjung Choi Tao Han OffRL 8 29 0 02 Nov 2021
Identifiable Generative Models for Missing Not at Random Data Imputation Chao Ma Cheng Zhang 28 33 0 27 Oct 2021
Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices Jan Povala Ieva Kazlauskaite Eky Febrianto F. Cirak Mark Girolami 11 22 0 22 Oct 2021
Predictive and Prescriptive Performance of Bike-Sharing Demand Forecasts for Inventory Management Daniele Gammelli Yihua Wang Dennis Prak Filipe Rodrigues Stefan Minner Francisco Câmara Pereira AI4TS 6 36 0 28 Jul 2021