Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches

12 March 2018

Yeming Wen

Paul Vicol

Jimmy Ba

Papers citing "Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches"

50 / 52 papers shown

Title
Exploring Channel Distinguishability in Local Neighborhoods of the Model Space in Quantum Neural Networks Sabrina Herbst S. S. Cranganore Vincenzo De Maio Ivona Brandić 50 0 0 17 Feb 2025
BLoB: Bayesian Low-Rank Adaptation by Backpropagation for Large Language Models Yibin Wang Haizhou Shi Ligong Han Dimitris N. Metaxas Hao Wang BDL UQLM 116 6 0 28 Jan 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 92 12 0 28 Jan 2025
Can Bayesian Neural Networks Explicitly Model Input Uncertainty? Matias Valdenegro-Toro Marco Zullich BDL PER UQCV UD 199 0 0 14 Jan 2025
WeiPer: OOD Detection using Weight Perturbations of Class Projections Maximilian Granz Manuel Heurich Tim Landgraf OODD 46 1 0 27 May 2024
Credal Wrapper of Model Averaging for Uncertainty Estimation in Classification Kaizheng Wang Fabio Cuzzolin Keivan K1 Shariatmadar David Moens Hans Hallez UQCV BDL 85 6 0 23 May 2024
Probabilistic Multi-Layer Perceptrons for Wind Farm Condition Monitoring Filippo Fiocchi Domna Ladopoulou P. Dellaportas 44 1 0 25 Apr 2024
Uncertainty Quantification for Gradient-based Explanations in Neural Networks Mihir Mulye Matias Valdenegro-Toro UQCV FAtt 33 0 0 25 Mar 2024
Attack Named Entity Recognition by Entity Boundary Interference Yifei Yang Hongqiu Wu Hai Zhao AAML 24 5 0 09 May 2023
Beyond In-Domain Scenarios: Robust Density-Aware Calibration Christian Tomani Futa Waseda Yuesong Shen Daniel Cremers UQCV 34 4 0 10 Feb 2023
Constraining cosmological parameters from N-body simulations with Variational Bayesian Neural Networks Héctor J. Hortúa L. '. García Leonardo Castañeda C. BDL 24 4 0 09 Jan 2023
Uncertainty Quantification for Deep Neural Networks: An Empirical Comparison and Usage Guidelines Michael Weiss Paolo Tonella BDL UQCV 19 11 0 14 Dec 2022
Hierarchically Structured Task-Agnostic Continual Learning Heinke Hihn Daniel A. Braun BDL CLL 19 8 0 14 Nov 2022
Do Bayesian Neural Networks Need To Be Fully Stochastic? Mrinank Sharma Sebastian Farquhar Eric T. Nalisnick Tom Rainforth BDL 23 52 0 11 Nov 2022
Disentangled Uncertainty and Out of Distribution Detection in Medical Generative Models Kumud Lakara Matias Valdenegro-Toro UQCV OOD 30 1 0 11 Nov 2022
A Benchmark for Out of Distribution Detection in Point Cloud 3D Semantic Segmentation Lokesh Veeramacheneni Matias Valdenegro-Toro 3DPC UQCV 22 2 0 11 Nov 2022
Comparison of Uncertainty Quantification with Deep Learning in Time Series Regression Levente Foldesi Matias Valdenegro-Toro UQCV 25 3 0 11 Nov 2022
Accelerated Linearized Laplace Approximation for Bayesian Deep Learning Zhijie Deng Feng Zhou Jun Zhu BDL 47 19 0 23 Oct 2022
Scaling Forward Gradient With Local Losses Mengye Ren Simon Kornblith Renjie Liao Geoffrey E. Hinton 81 49 0 07 Oct 2022
Shifts 2.0: Extending The Dataset of Real Distributional Shifts A. Malinin A. Athanasopoulos M. Barakovic Meritxell Bach Cuadra Mark J. F. Gales ... Francesco La Rosa Eli Sivena V. Tsarsitalidis Efi Tsompopoulou E. Volf OOD 24 28 0 30 Jun 2022
Image-based Treatment Effect Heterogeneity Connor Jerzak Fredrik D. Johansson Adel Daoud 32 20 0 13 Jun 2022
Leveraging Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations Maximilian Mueller Robin Greif Frank Jenko Nils Thuerey 24 3 0 02 May 2022
Joint Learning of Reward Machines and Policies in Environments with Partially Known Semantics Christos K. Verginis Cevahir Köprülü Sandeep P. Chinchali Ufuk Topcu 30 10 0 20 Apr 2022
A Deeper Look into Aleatoric and Epistemic Uncertainty Disentanglement Matias Valdenegro-Toro Daniel Saromo UD PER BDL UQCV 19 76 0 20 Apr 2022
A heteroencoder architecture for prediction of failure locations in porous metals using variational inference Wyatt Bridgman Xiaoxuan Zhang G. Teichert M. Khalil K. Garikipati Reese E. Jones UQCV AI4CE 18 5 0 31 Jan 2022
Constraining cosmological parameters from N-body simulations with Bayesian Neural Networks Héctor J. Hortúa BDL 20 1 0 22 Dec 2021
Benchmark for Out-of-Distribution Detection in Deep Reinforcement Learning Aaqib Parvez Mohammed Matias Valdenegro-Toro OOD OffRL 16 10 0 05 Dec 2021
Probabilistic Approach for Road-Users Detection Gledson Melotti Weihao Lu Pedro Conde Dezong Zhao A. Asvadi Nuno Gonçalves C. Premebida 27 2 0 02 Dec 2021
Exploring the Limits of Epistemic Uncertainty Quantification in Low-Shot Settings Matias Valdenegro-Toro UQCV 23 2 0 18 Nov 2021
Uncertainty Quantification in Neural Differential Equations Olga Graf P. Flores P. Protopapas K. Pichara UQCV AI4CE 31 7 0 08 Nov 2021
Pathologies in priors and inference for Bayesian transformers Tristan Cinquin Alexander Immer Max Horn Vincent Fortuin UQCV BDL MedIm 34 9 0 08 Oct 2021
TyXe: Pyro-based Bayesian neural nets for Pytorch H. Ritter Theofanis Karaletsos OOD MU BDL 26 6 0 01 Oct 2021
Uncertainty-Aware Reliable Text Classification Yibo Hu Latifur Khan EDL UQCV 33 33 0 15 Jul 2021
Laplace Redux -- Effortless Bayesian Deep Learning Erik A. Daxberger Agustinus Kristiadi Alexander Immer Runa Eschenhagen Matthias Bauer Philipp Hennig BDL UQCV 58 289 0 28 Jun 2021
Being a Bit Frequentist Improves Bayesian Neural Networks Agustinus Kristiadi Matthias Hein Philipp Hennig BDL UQCV 20 15 0 18 Jun 2021
Selective Probabilistic Classifier Based on Hypothesis Testing Saeed Bakhshi Germi Esa Rahtu H. Huttunen 22 1 0 09 May 2021
Uncertainty-Aware Self-Supervised Learning of Spatial Perception Tasks Mirko Nava Antonio Paolillo Jérôme Guzzi L. Gambardella Alessandro Giusti SSL 16 15 0 22 Mar 2021
Bayesian neural networks for weak solution of PDEs with uncertainty quantification Xiaoxuan Zhang K. Garikipati AI4CE 46 11 0 13 Jan 2021
Detecting and Adapting to Irregular Distribution Shifts in Bayesian Online Learning Aodong Li Alex Boyd Padhraic Smyth Stephan Mandt 15 21 0 15 Dec 2020
Delta-STN: Efficient Bilevel Optimization for Neural Networks using Structured Response Jacobians Juhan Bae Roger C. Grosse 27 24 0 26 Oct 2020
Toward Reliable Models for Authenticating Multimedia Content: Detecting Resampling Artifacts With Bayesian Neural Networks Anatol Maier Benedikt Lorch Christian Riess AAML 38 17 0 28 Jul 2020
Bayesian Few-Shot Classification with One-vs-Each Pólya-Gamma Augmented Gaussian Processes Jake C. Snell R. Zemel 33 63 0 20 Jul 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification F. Wenzel Jasper Snoek Dustin Tran Rodolphe Jenatton UQCV 33 203 0 24 Jun 2020
Bayesian Neural Networks at Scale: A Performance Analysis and Pruning Study Himanshu Sharma Elise Jennings BDL 27 3 0 23 May 2020
Parameters Estimation from the 21 cm signal using Variational Inference Héctor J. Hortúa Riccardo Volpi Luigi Malagò 11 2 0 04 May 2020
BatchEnsemble: An Alternative Approach to Efficient Ensemble and Lifelong Learning Yeming Wen Dustin Tran Jimmy Ba OOD FedML UQCV 27 482 0 17 Feb 2020
Deep Ensembles: A Loss Landscape Perspective Stanislav Fort Huiyi Hu Balaji Lakshminarayanan OOD UQCV 24 617 0 05 Dec 2019
Variational Federated Multi-Task Learning Luca Corinzia Ami Beuret J. M. Buhmann FedML 27 159 0 14 Jun 2019
Specifying Weight Priors in Bayesian Deep Neural Networks with Empirical Bayes R. Krishnan Mahesh Subedar Omesh Tickoo BDL 20 46 0 12 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 24 1,654 0 06 Jun 2019