MintNet: Building Invertible Neural Networks with Masked Convolutions

18 July 2019

Papers citing "MintNet: Building Invertible Neural Networks with Masked Convolutions"

24 / 24 papers shown

Title
Accelerate TarFlow Sampling with GS-Jacobi Iteration Ben Liu Zhen Qin 22 0 0 19 May 2025
Invertible Diffusion Models for Compressed Sensing Bin Chen Zhenyu Zhang Weiqi Li Chen Zhao Jiwen Yu Shijie Zhao Jie Chen Jian Zhang DiffM 59 5 0 25 Mar 2024
Classification Diffusion Models: Revitalizing Density Ratio Estimation Shahar Yadin Noam Elata T. Michaeli DiffM 48 1 0 15 Feb 2024
PaReprop: Fast Parallelized Reversible Backpropagation Tyler Lixuan Zhu K. Mangalam 19 1 0 15 Jun 2023
Training Energy-Based Normalizing Flow with Score-Matching Objectives Chen-Hao Chao Wei-Fang Sun Yen-Chang Hsu Z. Kira Chun-Yi Lee 33 3 0 24 May 2023
Certified Invertibility in Neural Networks via Mixed-Integer Programming Tianqi Cui Tom S. Bertalan George J. Pappas M. Morari Ioannis G. Kevrekidis Mahyar Fazlyab AAML 27 2 0 27 Jan 2023
$FInC Flow: Fast and Invertible $k \times k$ Convolutions for Normalizing Flows$ FInC Flow: Fast and Invertible $k \times k$ Convolutions for Normalizing Flows Aditya Kallappa Sandeep Nagar Girish Varma 27 2 0 23 Jan 2023
Re^2TAL: Rewiring Pretrained Video Backbones for Reversible Temporal Action Localization Chen Zhao Shuming Liu K. Mangalam Guohao Li 40 17 0 25 Nov 2022
SIReN-VAE: Leveraging Flows and Amortized Inference for Bayesian Networks Jacobie Mouton Steve Kroon DRL BDL 26 0 0 23 Apr 2022
A Compact Neural Network-based Algorithm for Robust Image Watermarking Hongcai Xu Rong Wang Jia Wei Shao-Ping Lu 29 13 0 27 Dec 2021
Featurized Density Ratio Estimation Kristy Choi Madeline Liao Stefano Ermon TPM 22 22 0 05 Jul 2021
Deep Generative Modelling: A Comparative Review of VAEs, GANs, Normalizing Flows, Energy-Based and Autoregressive Models Sam Bond-Taylor Adam Leach Yang Long Chris G. Willcocks VLM TPM 48 485 0 08 Mar 2021
Argmax Flows and Multinomial Diffusion: Learning Categorical Distributions Emiel Hoogeboom Didrik Nielsen P. Jaini Patrick Forré Max Welling DiffM 222 402 0 10 Feb 2021
Score-Based Generative Modeling through Stochastic Differential Equations Yang Song Jascha Narain Sohl-Dickstein Diederik P. Kingma Abhishek Kumar Stefano Ermon Ben Poole DiffM SyDa 96 6,126 0 26 Nov 2020
Understanding and Mitigating Exploding Inverses in Invertible Neural Networks Jens Behrmann Paul Vicol Kuan-Chieh Wang Roger C. Grosse J. Jacobsen 23 93 0 16 Jun 2020
The Convolution Exponential and Generalized Sylvester Flows Emiel Hoogeboom Victor Garcia Satorras Jakub M. Tomczak Max Welling 30 28 0 02 Jun 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 31 87 0 17 Feb 2020
Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving Yang Song Chenlin Meng Renjie Liao Stefano Ermon 17 28 0 10 Feb 2020
Learning Discrete Distributions by Dequantization Emiel Hoogeboom Taco S. Cohen Jakub M. Tomczak DRL 34 31 0 30 Jan 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 40 111 0 30 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 67 1,635 0 05 Dec 2019
FIS-GAN: GAN with Flow-based Importance Sampling Shiyu Yi Donglin Zhan Wenqing Zhang Zhengyang Geng Kang An Hao Wang GAN 29 3 0 06 Oct 2019
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference Jakob Kruse Gianluca Detommaso Ullrich Kothe Robert Scheichl 13 45 0 25 May 2019
Pixel Recurrent Neural Networks Aaron van den Oord Nal Kalchbrenner Koray Kavukcuoglu SSeg GAN 275 2,553 0 25 Jan 2016