Hybrid Models with Deep and Invertible Features

7 February 2019

Balaji Lakshminarayanan

BDL

DRL

ArXiv PDF HTML

Papers citing "Hybrid Models with Deep and Invertible Features"

20 / 20 papers shown

Title
Navigating Tabular Data Synthesis Research: Understanding User Needs and Tool Capabilities Maria F. Davila Sven Groen Fabian Panse Wolfram Wingerath LMTD 32 1 0 31 May 2024
A Causal Framework for Evaluating Deferring Systems Filippo Palomba Andrea Pugnana Jose M. Alvarez Salvatore Ruggieri CML 48 1 0 29 May 2024
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers Wanqian Yang Polina Kirichenko Micah Goldblum A. Wilson DRL 24 10 0 28 Nov 2022
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models Chen Liang Wenguan Wang Jiaxu Miao Yi Yang VLM 33 117 0 05 Oct 2022
Saliency Guided Adversarial Training for Learning Generalizable Features with Applications to Medical Imaging Classification System Xin Li Yao Qiang Chengyin Li Sijia Liu D. Zhu OOD MedIm 29 4 0 09 Sep 2022
Breaking Down Out-of-Distribution Detection: Many Methods Based on OOD Training Data Estimate a Combination of the Same Core Quantities Julian Bitterwolf Alexander Meinke Maximilian Augustin Matthias Hein OODD 15 25 0 20 Jun 2022
Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback Yuntao Bai Andy Jones Kamal Ndousse Amanda Askell Anna Chen ... Jack Clark Sam McCandlish C. Olah Benjamin Mann Jared Kaplan 72 2,308 0 12 Apr 2022
Featurized Density Ratio Estimation Kristy Choi Madeline Liao Stefano Ermon TPM 14 22 0 05 Jul 2021
Task-agnostic Continual Learning with Hybrid Probabilistic Models Polina Kirichenko Mehrdad Farajtabar Dushyant Rao Balaji Lakshminarayanan Nir Levine Ang Li Huiyi Hu A. Wilson Razvan Pascanu VLM BDL CLL 14 19 0 24 Jun 2021
On Batch Normalisation for Approximate Bayesian Inference Jishnu Mukhoti P. Dokania Philip H. S. Torr Y. Gal BDL UQCV 29 4 0 24 Dec 2020
Contrastive Training for Improved Out-of-Distribution Detection Jim Winkens Rudy Bunel Abhijit Guha Roy Robert Stanforth Vivek Natarajan ... Alan Karthikesalingam Simon A. A. Kohl taylan. cemgil S. M. Ali Eslami Olaf Ronneberger OODD 11 234 0 10 Jul 2020
Ordering Dimensions with Nested Dropout Normalizing Flows Artur Bekasov Iain Murray DRL 17 5 0 15 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 33 100 0 15 Jun 2020
Uncertainty Estimation Using a Single Deep Deterministic Neural Network Joost R. van Amersfoort Lewis Smith Yee Whye Teh Y. Gal UQCV BDL 14 55 0 04 Mar 2020
Augmented Normalizing Flows: Bridging the Gap Between Generative Flows and Latent Variable Models Chin-Wei Huang Laurent Dinh Aaron Courville DRL 24 87 0 17 Feb 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 22 111 0 30 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 20 9 0 09 Dec 2019
Likelihood Ratios for Out-of-Distribution Detection Jie Jessie Ren Peter J. Liu Emily Fertig Jasper Snoek Ryan Poplin M. DePristo Joshua V. Dillon Balaji Lakshminarayanan OODD 18 716 0 07 Jun 2019
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen D. Duvenaud J. Jacobsen UQCV TPM 20 617 0 02 Nov 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 270 5,660 0 05 Dec 2016