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"

28 / 28 papers shown

Title
Measurement to Meaning: A Validity-Centered Framework for AI Evaluation Olawale Salaudeen Anka Reuel Ahmed M. Ahmed Suhana Bedi Zachary Robertson Shri Kiran Srinivasan Ben Domingue Angelina Wang Sanmi Koyejo ELM 27 1 0 13 May 2025
Navigating Tabular Data Synthesis Research: Understanding User Needs and Tool Capabilities Maria F. Davila Sven Groen Fabian Panse Wolfram Wingerath LMTD 39 1 0 31 May 2024
A Causal Framework for Evaluating Deferring Systems Filippo Palomba Andrea Pugnana Jose M. Alvarez Salvatore Ruggieri CML 59 3 0 29 May 2024
Learning Data Representations with Joint Diffusion Models Kamil Deja Tomasz Trzciñski Jakub M. Tomczak DiffM 30 15 0 31 Jan 2023
Chroma-VAE: Mitigating Shortcut Learning with Generative Classifiers Wanqian Yang Polina Kirichenko Micah Goldblum A. Wilson DRL 30 10 0 28 Nov 2022
GMMSeg: Gaussian Mixture based Generative Semantic Segmentation Models Chen Liang Wenguan Wang Jiaxu Miao Yi Yang VLM 46 117 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 42 4 0 09 Sep 2022
Your ViT is Secretly a Hybrid Discriminative-Generative Diffusion Model Xiulong Yang Sheng-Min Shih Yinlin Fu Xiaoting Zhao Shihao Ji DiffM 33 56 0 16 Aug 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 21 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 110 2,352 0 12 Apr 2022
Featurized Density Ratio Estimation Kristy Choi Madeline Liao Stefano Ermon TPM 22 22 0 05 Jul 2021
On the Practicality of Deterministic Epistemic Uncertainty Janis Postels Mattia Segu Tao Sun Luca Sieber Luc Van Gool Feng Yu Federico Tombari UQCV 38 60 0 01 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 27 19 0 24 Jun 2021
On Batch Normalisation for Approximate Bayesian Inference Jishnu Mukhoti P. Dokania Philip Torr Y. Gal BDL UQCV 29 4 0 24 Dec 2020
Further Analysis of Outlier Detection with Deep Generative Models Ziyu Wang Bin Dai David Wipf Jun Zhu 17 39 0 25 Oct 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 19 236 0 10 Jul 2020
Ordering Dimensions with Nested Dropout Normalizing Flows Artur Bekasov Iain Murray DRL 28 5 0 15 Jun 2020
Depth Uncertainty in Neural Networks Javier Antorán J. Allingham José Miguel Hernández-Lobato UQCV OOD BDL 46 100 0 15 Jun 2020
Hybrid Models for Open Set Recognition Hongjie Zhang Ang Li Jie Guo Yanwen Guo BDL 28 184 0 27 Mar 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 31 87 0 17 Feb 2020
Semi-Supervised Learning with Normalizing Flows Pavel Izmailov Polina Kirichenko Marc Finzi A. Wilson DRL BDL 40 111 0 30 Dec 2019
InfoCNF: An Efficient Conditional Continuous Normalizing Flow with Adaptive Solvers T. Nguyen Animesh Garg Richard G. Baraniuk Anima Anandkumar TPM 28 9 0 09 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
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 50 717 0 07 Jun 2019
Can You Trust Your Model's Uncertainty? Evaluating Predictive Uncertainty Under Dataset Shift Yaniv Ovadia Emily Fertig Jie Jessie Ren Zachary Nado D. Sculley Sebastian Nowozin Joshua V. Dillon Balaji Lakshminarayanan Jasper Snoek UQCV 77 1,662 0 06 Jun 2019
Invertible Residual Networks Jens Behrmann Will Grathwohl Ricky T. Q. Chen David Duvenaud J. Jacobsen UQCV TPM 37 618 0 02 Nov 2018
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 278 5,695 0 05 Dec 2016