On the challenges of learning with inference networks on sparse,
high-dimensional data

On the challenges of learning with inference networks on sparse, high-dimensional data

17 October 2017

Rahul G. Krishnan

Matthew Hoffman

Papers citing "On the challenges of learning with inference networks on sparse, high-dimensional data"

17 / 17 papers shown

Title
ParamReL: Learning Parameter Space Representation via Progressively Encoding Bayesian Flow Networks Zhangkai Wu Xuhui Fan Jin Li Zhilin Zhao Hui Chen LongBing Cao 57 2 0 24 May 2024
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran Babak Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 28 5 0 09 Feb 2023
Hyperspectral Image Compression Using Implicit Neural Representation Shima Rezasoltani Faisal Z. Qureshi 12 5 0 08 Feb 2023
Prior Density Learning in Variational Bayesian Phylogenetic Parameters Inference Amine M. Remita Golrokh Vitae Abdoulaye Baniré Diallo BDL 21 0 0 06 Feb 2023
Variational Laplace Autoencoders Yookoon Park C. Kim Gunhee Kim BDL DRL 26 21 0 30 Nov 2022
Compressive Features in Offline Reinforcement Learning for Recommender Systems Hung Nguyen Minh Nguyen Long Pham Jennifer Adorno Nieves OffRL 18 2 0 16 Nov 2021
Stochastic Iterative Graph Matching Linfeng Liu M. C. Hughes S. Hassoun Liping Liu 27 15 0 04 Jun 2021
COIN: COmpression with Implicit Neural representations Emilien Dupont Adam Goliñski Milad Alizadeh Yee Whye Teh Arnaud Doucet 23 223 0 03 Mar 2021
Preconditioned training of normalizing flows for variational inference in inverse problems Ali Siahkoohi G. Rizzuti M. Louboutin Philipp A. Witte Felix J. Herrmann 75 32 0 11 Jan 2021
Control as Hybrid Inference Alexander Tschantz Beren Millidge A. Seth Christopher L. Buckley 19 9 0 11 Jul 2020
Going in circles is the way forward: the role of recurrence in visual inference R. S. V. Bergen N. Kriegeskorte 17 82 0 26 Mar 2020
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 32 20 0 10 Mar 2019
Lagging Inference Networks and Posterior Collapse in Variational Autoencoders Junxian He Daniel M. Spokoyny Graham Neubig Taylor Berg-Kirkpatrick BDL DRL 25 272 0 16 Jan 2019
Good Initializations of Variational Bayes for Deep Models Simone Rossi Pietro Michiardi Maurizio Filippone BDL 17 21 0 18 Oct 2018
Iterative Amortized Inference Joseph Marino Yisong Yue Stephan Mandt BDL DRL 23 165 0 24 Jul 2018
Semi-Amortized Variational Autoencoders Yoon Kim Sam Wiseman Andrew C. Miller David Sontag Alexander M. Rush BDL DRL 33 243 0 07 Feb 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li David Duvenaud DRL BDL 33 280 0 10 Jan 2018