Semantic uncertainty intervals for disentangled latent spaces

20 July 2022

S. Sankaranarayanan

Anastasios Nikolas Angelopoulos

Papers citing "Semantic uncertainty intervals for disentangled latent spaces"

23 / 23 papers shown

Title
Generative Uncertainty in Diffusion Models Metod Jazbec Eliot Wong-Toi Guoxuan Xia Dan Zhang Eric T. Nalisnick Stephan Mandt DiffM 38 0 0 28 Feb 2025
Conformal Prediction: A Data Perspective Xiaofan Zhou Baiting Chen Yu Gui Lu Cheng 42 2 0 09 Oct 2024
Bridging Model Heterogeneity in Federated Learning via Uncertainty-based Asymmetrical Reciprocity Learning Jiaqi Wang Chenxu Zhao Lingjuan Lyu Quanzeng You Mengdi Huai Fenglong Ma FedML 23 3 0 03 Jul 2024
Fast yet Safe: Early-Exiting with Risk Control Metod Jazbec Alexander Timans Tin Hadvzi Veljković K. Sakmann Dan Zhang C. A. Naesseth Eric T. Nalisnick 25 5 0 31 May 2024
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction Jeffrey Wen Rizwan Ahmad Philip Schniter 18 1 0 28 May 2024
Uncertainty Visualization via Low-Dimensional Posterior Projections Omer Yair E. Nehme T. Michaeli UQCV 17 2 0 12 Dec 2023
Prompt Risk Control: A Rigorous Framework for Responsible Deployment of Large Language Models Thomas P. Zollo Todd Morrill Zhun Deng Jake C. Snell T. Pitassi Richard Zemel 25 8 0 22 Nov 2023
From Posterior Sampling to Meaningful Diversity in Image Restoration Noa Cohen Hila Manor Yuval Bahat T. Michaeli DiffM 14 10 0 24 Oct 2023
Risk-Aware and Explainable Framework for Ensuring Guaranteed Coverage in Evolving Hardware Trojan Detection Rahul Vishwakarma Amin Rezaei 21 5 0 14 Oct 2023
Uncertainty Quantification via Neural Posterior Principal Components E. Nehme Omer Yair T. Michaeli UQCV 8 6 0 27 Sep 2023
On the Posterior Distribution in Denoising: Application to Uncertainty Quantification Hila Manor T. Michaeli UQCV 10 17 0 24 Sep 2023
Federated Conformal Predictors for Distributed Uncertainty Quantification Charles Lu Yaodong Yu Sai Praneeth Karimireddy Michael I. Jordan Ramesh Raskar FedML 15 21 0 27 May 2023
Principal Uncertainty Quantification with Spatial Correlation for Image Restoration Problems Omer Belhasin Yaniv Romano Daniel Freedman Ehud Rivlin Michael Elad 14 21 0 17 May 2023
What's Behind the Mask: Estimating Uncertainty in Image-to-Image Problems Gilad Kutiel Regev Cohen Michael Elad Daniel Freedman UQCV 6 5 0 28 Nov 2022
Conffusion: Confidence Intervals for Diffusion Models Eliahu Horwitz Yedid Hoshen DiffM 8 27 0 17 Nov 2022
Conformal Risk Control Anastasios Nikolas Angelopoulos Stephen Bates Adam Fisch Lihua Lei Tal Schuster 22 87 0 04 Aug 2022
Learn then Test: Calibrating Predictive Algorithms to Achieve Risk Control Anastasios Nikolas Angelopoulos Stephen Bates Emmanuel J. Candès Michael I. Jordan Lihua Lei 86 125 0 03 Oct 2021
Few-shot Conformal Prediction with Auxiliary Tasks Adam Fisch Tal Schuster Tommi Jaakkola Regina Barzilay 176 53 0 17 Feb 2021
Designing an Encoder for StyleGAN Image Manipulation Omer Tov Yuval Alaluf Yotam Nitzan Or Patashnik Daniel Cohen-Or 188 651 0 04 Feb 2021
Distribution-Free, Risk-Controlling Prediction Sets Stephen Bates Anastasios Nikolas Angelopoulos Lihua Lei Jitendra Malik Michael I. Jordan OOD 173 184 0 07 Jan 2021
PULSE: Self-Supervised Photo Upsampling via Latent Space Exploration of Generative Models Sachit Menon Alexandru Damian Shijia Hu Nikhil Ravi Cynthia Rudin OOD DiffM 180 536 0 08 Mar 2020
A Style-Based Generator Architecture for Generative Adversarial Networks Tero Karras S. Laine Timo Aila 262 10,183 0 12 Dec 2018
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,042 0 06 Jun 2015