Semi-Supervised Learning with Normalizing Flows

30 December 2019

Papers citing "Semi-Supervised Learning with Normalizing Flows"

26 / 76 papers shown

Title
Input Invex Neural Network Suman Sapkota Binod Bhattarai 11 4 0 16 Jun 2021
Go with the Flows: Mixtures of Normalizing Flows for Point Cloud Generation and Reconstruction Janis Postels Mengya Liu Riccardo Spezialetti Luc Van Gool Federico Tombari AI4CE 3DPC 6 22 0 06 Jun 2021
On Training Sample Memorization: Lessons from Benchmarking Generative Modeling with a Large-scale Competition C. Bai Hsuan-Tien Lin Colin Raffel Wendy Kan 16 34 0 06 Jun 2021
Semi-supervised Learning with Missing Values Imputation Buliao Huang Yunhui Zhu Muhammad Usman Huanhuan Chen 8 11 0 03 Jun 2021
LiftPool: Bidirectional ConvNet Pooling Jiaojiao Zhao Cees G. M. Snoek 8 19 0 02 Apr 2021
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation Chris Waites Rachel Cummings 12 15 0 25 Mar 2021
ECINN: Efficient Counterfactuals from Invertible Neural Networks Frederik Hvilshoj Alexandros Iosifidis Ira Assent BDL 16 26 0 25 Mar 2021
DOC2PPT: Automatic Presentation Slides Generation from Scientific Documents Tsu-jui Fu W. Wang Daniel J. McDuff Yale Song 14 49 0 28 Jan 2021
TabTransformer: Tabular Data Modeling Using Contextual Embeddings Xin Huang A. Khetan Milan Cvitkovic Zohar S. Karnin ViT LMTD 145 416 0 11 Dec 2020
Measure Transport with Kernel Stein Discrepancy Matthew A. Fisher T. Nolan Matthew M. Graham D. Prangle Chris J. Oates OT 25 15 0 22 Oct 2020
Semi-supervised Learning by Latent Space Energy-Based Model of Symbol-Vector Coupling Bo Pang Erik Nijkamp Jiali Cui Tian Han Ying Nian Wu SSL 27 4 0 19 Oct 2020
A Contrastive Learning Approach for Training Variational Autoencoder Priors J. Aneja A. Schwing Jan Kautz Arash Vahdat DRL 6 81 0 06 Oct 2020
VAEBM: A Symbiosis between Variational Autoencoders and Energy-based Models Zhisheng Xiao Karsten Kreis Jan Kautz Arash Vahdat 11 123 0 01 Oct 2020
Variational Mixture of Normalizing Flows Guilherme G. P. Freitas Pires Mário A. T. Figueiredo BDL DRL 10 16 0 01 Sep 2020
Generative Classifiers as a Basis for Trustworthy Image Classification Radek Mackowiak Lynton Ardizzone Ullrich Kothe Carsten Rother 6 4 0 29 Jul 2020
Coupling-based Invertible Neural Networks Are Universal Diffeomorphism Approximators Takeshi Teshima Isao Ishikawa Koichi Tojo Kenta Oono Masahiro Ikeda Masashi Sugiyama 17 110 0 20 Jun 2020
Why Normalizing Flows Fail to Detect Out-of-Distribution Data Polina Kirichenko Pavel Izmailov A. Wilson OODD 11 271 0 15 Jun 2020
An Improved Semi-Supervised VAE for Learning Disentangled Representations Weili Nie Zichao Wang Ankit B. Patel Richard G. Baraniuk CoGe DRL 11 4 0 12 Jun 2020
Robust model training and generalisation with Studentising flows Simon Alexanderson G. Henter OOD 6 13 0 11 Jun 2020
Likelihood Assignment for Out-of-Distribution Inputs in Deep Generative Models is Sensitive to Prior Distribution Choice Ryo Kamoi Kei Kobayashi 18 2 0 15 Nov 2019
Likelihood Contribution based Multi-scale Architecture for Generative Flows Hari Prasanna Das Pieter Abbeel C. Spanos DRL AI4CE 12 5 0 05 Aug 2019
Deep Invertible Networks for EEG-based brain-signal decoding R. Schirrmeister T. Ball 9 0 0 17 Jul 2019
Understanding the Limitations of Conditional Generative Models Ethan Fetaya J. Jacobsen Will Grathwohl R. Zemel 11 53 0 04 Jun 2019
Semi-Conditional Normalizing Flows for Semi-Supervised Learning Andrei Atanov Alexandra Volokhova Arsenii Ashukha Ivan Sosnovik Dmitry Vetrov BDL 13 41 0 01 May 2019
There Are Many Consistent Explanations of Unlabeled Data: Why You Should Average Ben Athiwaratkun Marc Finzi Pavel Izmailov A. Wilson 199 243 0 14 Jun 2018
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 230 2,545 0 25 Jan 2016