On the Quantitative Analysis of Decoder-Based Generative Models

14 November 2016

Papers citing "On the Quantitative Analysis of Decoder-Based Generative Models"

35 / 35 papers shown

Title
Matching aggregate posteriors in the variational autoencoder Surojit Saha Sarang Joshi Ross T. Whitaker DRL 16 4 0 13 Nov 2023
Steering Language Generation: Harnessing Contrastive Expert Guidance and Negative Prompting for Coherent and Diverse Synthetic Data Generation Charles OÑeill Y. Ting 丁 I. Ciucă Jack Miller Thang Bui SyDa 31 1 0 15 Aug 2023
Compositional diversity in visual concept learning Yanli Zhou Reuben Feinman Brenden Lake CoGe OCL 24 8 0 30 May 2023
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images Matthew D. Hoffman T. Le Pavel Sountsov Christopher Suter Ben Lee Vikash K. Mansinghka Rif A. Saurous BDL 24 12 0 27 Oct 2022
Optimization of Annealed Importance Sampling Hyperparameters Shirin Goshtasbpour F. Pérez-Cruz 19 1 0 27 Sep 2022
Deterministic Langevin Monte Carlo with Normalizing Flows for Bayesian Inference R. Grumitt B. Dai U. Seljak BDL 24 12 0 27 May 2022
Variational Inference with Locally Enhanced Bounds for Hierarchical Models Tomas Geffner Justin Domke 16 5 0 08 Mar 2022
Generative Adversarial Networks and Adversarial Autoencoders: Tutorial and Survey Benyamin Ghojogh A. Ghodsi Fakhri Karray Mark Crowley GAN 26 12 0 26 Nov 2021
NEO: Non Equilibrium Sampling on the Orbit of a Deterministic Transform Achille Thin Yazid Janati Sylvain Le Corff Charles Ollion Arnaud Doucet Alain Durmus Eric Moulines C. Robert 15 7 0 17 Mar 2021
How Faithful is your Synthetic Data? Sample-level Metrics for Evaluating and Auditing Generative Models Ahmed Alaa B. V. Breugel Evgeny S. Saveliev M. Schaar 45 186 0 17 Feb 2021
On the Evaluation of Generative Adversarial Networks By Discriminative Models A. Torfi Mohammadreza Beyki Edward A. Fox EGVM 11 7 0 07 Oct 2020
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks Yaniv Yacoby Weiwei Pan Finale Doshi-Velez CML DRL 16 24 0 14 Jul 2020
Pretraining Image Encoders without Reconstruction via Feature Prediction Loss G. Pihlgren Fredrik Sandin Marcus Liwicki 8 3 0 16 Mar 2020
Towards GAN Benchmarks Which Require Generalization Ishaan Gulrajani Colin Raffel Luke Metz 11 57 0 10 Jan 2020
Improving Image Autoencoder Embeddings with Perceptual Loss G. Pihlgren Fredrik Sandin Marcus Liwicki 17 33 0 10 Jan 2020
Seeing What a GAN Cannot Generate David Bau Jun-Yan Zhu Jonas Wulff William S. Peebles Hendrik Strobelt Bolei Zhou Antonio Torralba GAN 17 307 0 24 Oct 2019
Prescribed Generative Adversarial Networks Adji Bousso Dieng Francisco J. R. Ruiz David M. Blei Michalis K. Titsias GAN DRL 19 61 0 09 Oct 2019
NeuTra-lizing Bad Geometry in Hamiltonian Monte Carlo Using Neural Transport Matthew Hoffman Pavel Sountsov Joshua V. Dillon I. Langmore Dustin Tran Srinivas Vasudevan BDL 18 103 0 09 Mar 2019
Spread Divergence Mingtian Zhang Peter Hayes Thomas Bird Raza Habib David Barber MedIm UD 30 20 0 21 Nov 2018
Entropic GANs meet VAEs: A Statistical Approach to Compute Sample Likelihoods in GANs Yogesh Balaji Hamed Hassani Rama Chellappa S. Feizi GAN DRL 30 20 0 09 Oct 2018
Assessing Generative Models via Precision and Recall Mehdi S. M. Sajjadi Olivier Bachem Mario Lucic Olivier Bousquet Sylvain Gelly EGVM 8 565 0 31 May 2018
On GANs and GMMs Eitan Richardson Yair Weiss GAN 15 149 0 31 May 2018
Quantitatively Evaluating GANs With Divergences Proposed for Training Daniel Jiwoong Im He Ma Graham W. Taylor K. Branson EGVM 13 69 0 02 Mar 2018
PBGen: Partial Binarization of Deconvolution-Based Generators for Edge Intelligence Jinglan Liu Jiaxin Zhang Yukun Ding Xiaowei Xu Meng-Long Jiang Yiyu Shi 22 4 0 26 Feb 2018
Is Generator Conditioning Causally Related to GAN Performance? Augustus Odena Jacob Buckman Catherine Olsson Tom B. Brown C. Olah Colin Raffel Ian Goodfellow AI4CE 14 112 0 23 Feb 2018
Inference Suboptimality in Variational Autoencoders Chris Cremer Xuechen Li D. Duvenaud DRL BDL 11 281 0 10 Jan 2018
Faithful Inversion of Generative Models for Effective Amortized Inference Stefan Webb Adam Goliñski R. Zinkov Siddharth Narayanaswamy Tom Rainforth Yee Whye Teh Frank D. Wood TPM 24 46 0 01 Dec 2017
PassGAN: A Deep Learning Approach for Password Guessing B. Hitaj Paolo Gasti G. Ateniese F. Pérez-Cruz GAN 22 246 0 01 Sep 2017
Comparison of Maximum Likelihood and GAN-based training of Real NVPs Ivo Danihelka Balaji Lakshminarayanan Benigno Uria Daan Wierstra Peter Dayan GAN 11 53 0 15 May 2017
Boundary-Seeking Generative Adversarial Networks R. Devon Hjelm Athul Paul Jacob Tong Che Adam Trischler Kyunghyun Cho Yoshua Bengio GAN 11 170 0 27 Feb 2017
Adversarial Variational Bayes: Unifying Variational Autoencoders and Generative Adversarial Networks L. Mescheder Sebastian Nowozin Andreas Geiger GAN BDL 29 525 0 17 Jan 2017
Generative Adversarial Parallelization Daniel Jiwoong Im He Ma C. Kim Graham W. Taylor GAN 22 38 0 13 Dec 2016
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 23 412 0 11 Oct 2016
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 227 2,545 0 25 Jan 2016
MCMC using Hamiltonian dynamics Radford M. Neal 173 3,260 0 09 Jun 2012