Posterior Collapse and Latent Variable Non-identifiability

Neural Information Processing Systems (NeurIPS), 2023

2 January 2023

Papers citing "Posterior Collapse and Latent Variable Non-identifiability"

26 / 26 papers shown

Title
Disentangling Score Content and Performance Style for Joint Piano Rendering and Transcription Wei Zeng Junchuan Zhao Ye Wang 92 0 0 28 Sep 2025
Global Variational Inference Enhanced Robust Domain Adaptation Lingkun Luo Shiqiang Hu Liming Chen OOD 116 0 0 04 Jul 2025
DeepRV: Accelerating spatiotemporal inference with pre-trained neural priors Jhonathan Navott Daniel Jenson Seth Flaxman Elizaveta Semenova 232 0 0 27 Mar 2025
DeCaFlow: A deconfounding causal generative model Alejandro Almodóvar Adrián Javaloy J. Parras Santiago Zazo Isabel Valera CML 317 0 0 19 Mar 2025
Video prediction using score-based conditional density estimation P. Fiquet Eero P. Simoncelli AI4TS 128 0 0 30 Oct 2024
Transferring disentangled representations: bridging the gap between synthetic and real imagesNeural Information Processing Systems (NeurIPS), 2024 Jacopo Dapueto Nicoletta Noceti Francesca Odone OOD 386 2 0 26 Sep 2024
Remove Symmetries to Control Model Expressivity and Improve OptimizationInternational Conference on Learning Representations (ICLR), 2024 Liu Ziyin Yizhou Xu Isaac Chuang AAML 453 4 0 28 Aug 2024
Particle Semi-Implicit Variational Inference Jen Ning Lim A. M. Johansen 339 11 0 30 Jun 2024
Preventing Model Collapse in Gaussian Process Latent Variable ModelsInternational Conference on Machine Learning (ICML), 2024 Ying Li Zhidi Lin Feng Yin Michael Minyi Zhang VLM 209 3 0 02 Apr 2024
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders Yaniv Yacoby Weiwei Pan Finale Doshi-Velez DRL 356 0 0 13 Mar 2024
Nonparametric Automatic Differentiation Variational Inference with Spline ApproximationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024 Yuda Shao Shan Yu Tianshu Feng 192 2 0 10 Mar 2024
Learning Interpretable Concepts: Unifying Causal Representation Learning and Foundation Models Goutham Rajendran Simon Buchholz Bryon Aragam Bernhard Schölkopf Pradeep Ravikumar AI4CE 366 28 0 14 Feb 2024
Bayesian Transfer Learning Piotr M. Suder Jason Xu David B. Dunson 231 11 0 20 Dec 2023
Causal Dynamic Variational Autoencoder for Counterfactual Regression in Longitudinal Data Mouad El Bouchattaoui Myriam Tami Benoit Lepetit P. Cournède CML OOD 402 2 0 16 Oct 2023
Learning nonparametric latent causal graphs with unknown interventionsNeural Information Processing Systems (NeurIPS), 2023 Yibo Jiang Bryon Aragam CML 238 28 0 05 Jun 2023
Controlling Posterior Collapse by an Inverse Lipschitz Constraint on the Decoder NetworkInternational Conference on Machine Learning (ICML), 2023 Yuri Kinoshita Kenta Oono Kenji Fukumizu Yuichi Yoshida S. Maeda DRL BDL 191 4 0 25 Apr 2023
Discouraging posterior collapse in hierarchical Variational Autoencoders using context Anna Kuzina Jakub M. Tomczak BDL DRL 301 1 0 20 Feb 2023
GFlowNet-EM for learning compositional latent variable modelsInternational Conference on Machine Learning (ICML), 2023 J. E. Hu Nikolay Malkin Moksh Jain Katie Everett Alexandros Graikos Yoshua Bengio CoGe 223 45 0 13 Feb 2023
Language as a Latent Sequence: deep latent variable models for semi-supervised paraphrase generationAI Open (AO), 2023 Jialin Yu Alexandra I. Cristea Anoushka Harit Zhongtian Sun O. Aduragba Lei Shi Noura Al Moubayed VLM BDL DRL 215 3 0 05 Jan 2023
On the detrimental effect of invariances in the likelihood for variational inferenceNeural Information Processing Systems (NeurIPS), 2022 Richard Kurle R. Herbrich Tim Januschowski Bernie Wang Jan Gasthaus 200 9 0 15 Sep 2022
Identifiability of deep generative models without auxiliary informationNeural Information Processing Systems (NeurIPS), 2022 Bohdan Kivva Goutham Rajendran Pradeep Ravikumar Bryon Aragam DRL 274 61 0 20 Jun 2022
Indeterminacy in Generative Models: Characterization and Strong IdentifiabilityInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Quanhan Xi Benjamin Bloem-Reddy 292 30 0 02 Jun 2022
Posterior Collapse of a Linear Latent Variable ModelNeural Information Processing Systems (NeurIPS), 2022 Zihao Wang Liu Ziyin BDL 197 23 0 09 May 2022
Robust Policy Learning over Multiple Uncertainty SetsInternational Conference on Machine Learning (ICML), 2022 Annie Xie Shagun Sodhani Chelsea Finn Joelle Pineau Amy Zhang OOD OffRL 268 23 0 14 Feb 2022
Missing Data Imputation and Acquisition with Deep Hierarchical Models and Hamiltonian Monte CarloNeural Information Processing Systems (NeurIPS), 2022 I. Peis Chao Ma José Miguel Hernández-Lobato BDL DRL 412 21 0 09 Feb 2022
Deviance Matrix FactorizationElectronic Journal of Statistics (EJS), 2021 Liang Wang Luis Carvalho 102 8 0 12 Oct 2021