Bayesian Model Selection, the Marginal Likelihood, and Generalization

23 February 2022

Papers citing "Bayesian Model Selection, the Marginal Likelihood, and Generalization"

43 / 43 papers shown

Title
Learning Decision Trees as Amortized Structure Inference Mohammed Mahfoud Ghait Boukachab Michał Koziarski A. Garcia Stefan Bauer Yoshua Bengio Nikolay Malkin BDL 40 0 0 10 Mar 2025
Deep Learning is Not So Mysterious or Different Andrew Gordon Wilson 36 1 0 03 Mar 2025
Learning the Regularization Strength for Deep Fine-Tuning via a Data-Emphasized Variational Objective Ethan Harvey Mikhail Petrov Michael C. Hughes 37 0 0 28 Jan 2025
Identifying Information from Observations with Uncertainty and Novelty D. Prijatelj Timothy J. Ireland Walter J. Scheirer 48 0 0 16 Jan 2025
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks: An Extended Investigation Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 20 6 0 05 Jun 2024
Preventing Model Collapse in Gaussian Process Latent Variable Models Ying Li Zhidi Lin Feng Yin Michael Minyi Zhang VLM 20 1 0 02 Apr 2024
Bayesian Exploration of Pre-trained Models for Low-shot Image Classification Yibo Miao Yu Lei Feng Zhou Zhijie Deng VLM UQCV BDL 30 1 0 30 Mar 2024
Gaussian-process-regression-based method for the localization of exceptional points in complex resonance spectra Patrick Egenlauf Patric Rommel Jorg Main 14 1 0 07 Feb 2024
Position: Bayesian Deep Learning is Needed in the Age of Large-Scale AI Theodore Papamarkou Maria Skoularidou Konstantina Palla Laurence Aitchison Julyan Arbel ... David Rügamer Yee Whye Teh Max Welling Andrew Gordon Wilson Ruqi Zhang UQCV BDL 32 27 0 01 Feb 2024
Detecting Face Synthesis Using a Concealed Fusion Model Roberto Leyva Victor Sanchez Gregory Epiphaniou Carsten Maple AAML CVBM 20 0 0 08 Jan 2024
Data-Agnostic Face Image Synthesis Detection Using Bayesian CNNs Roberto Leyva Victor Sanchez Gregory Epiphaniou Carsten Maple CVBM 13 5 0 08 Jan 2024
PAC-Bayes-Chernoff bounds for unbounded losses Ioar Casado Luis A. Ortega A. Masegosa Aritz Pérez Martínez 14 6 0 02 Jan 2024
Bootstrap Your Own Variance Polina Turishcheva Jason Ramapuram Sinead Williamson Dan Busbridge Eeshan Gunesh Dhekane Russ Webb UQCV 11 0 0 06 Dec 2023
A PAC-Bayesian Perspective on the Interpolating Information Criterion Liam Hodgkinson Christopher van der Heide Roberto Salomone Fred Roosta Michael W. Mahoney 14 1 0 13 Nov 2023
TIC-TAC: A Framework for Improved Covariance Estimation in Deep Heteroscedastic Regression Megh Shukla Mathieu Salzmann Alexandre Alahi 11 3 0 29 Oct 2023
Leveraging Self-Consistency for Data-Efficient Amortized Bayesian Inference Marvin Schmitt Desi R. Ivanova Daniel Habermann Baixu Chen Jie Jiang Stefan T. Radev FedML 14 4 0 06 Oct 2023
A Primer on Bayesian Neural Networks: Review and Debates Federico Danieli Konstantinos Pitas M. Vladimirova Vincent Fortuin BDL AAML 48 18 0 28 Sep 2023
Amortised Inference in Bayesian Neural Networks Tommy Rochussen UQCV BDL 17 0 0 06 Sep 2023
Gibbs-Based Information Criteria and the Over-Parameterized Regime Haobo Chen Yuheng Bu Greg Wornell 14 1 0 08 Jun 2023
Improving Hyperparameter Learning under Approximate Inference in Gaussian Process Models Rui Li S. T. John Arno Solin BDL 15 3 0 07 Jun 2023
Adaptive Robotic Information Gathering via Non-Stationary Gaussian Processes Weizhe (Wesley) Chen R. Khardon Lantao Liu 9 9 0 02 Jun 2023
Approximate Bayesian Class-Conditional Models under Continuous Representation Shift Thomas L. Lee Amos Storkey BDL 17 3 0 30 May 2023
Hyperparameter Optimization through Neural Network Partitioning Bruno Mlodozeniec M. Reisser Christos Louizos 19 6 0 28 Apr 2023
The No Free Lunch Theorem, Kolmogorov Complexity, and the Role of Inductive Biases in Machine Learning Micah Goldblum Marc Finzi K. Rowan A. Wilson UQCV FedML 11 37 0 11 Apr 2023
In all LikelihoodS: How to Reliably Select Pseudo-Labeled Data for Self-Training in Semi-Supervised Learning Julian Rodemann Christoph Jansen G. Schollmeyer Thomas Augustin 10 0 0 02 Mar 2023
Sharp Calibrated Gaussian Processes A. Capone Geoff Pleiss Sandra Hirche UQCV 18 4 0 23 Feb 2023
Guided Deep Kernel Learning Idan Achituve Gal Chechik Ethan Fetaya BDL 21 4 0 19 Feb 2023
Approximately Bayes-Optimal Pseudo Label Selection Julian Rodemann Jann Goschenhofer Emilio Dorigatti T. Nagler Thomas Augustin 11 8 0 17 Feb 2023
A Deep Learning Method for Comparing Bayesian Hierarchical Models Lasse Elsemüller Martin Schnuerch Paul-Christian Burkner Stefan T. Radev BDL 9 9 0 27 Jan 2023
Bayesian Interpolation with Deep Linear Networks Boris Hanin Alexander Zlokapa 21 25 0 29 Dec 2022
Are you using test log-likelihood correctly? Sameer K. Deshpande Soumya K. Ghosh Tin D. Nguyen Tamara Broderick 11 7 0 01 Dec 2022
An Empirical Analysis of the Advantages of Finite- v.s. Infinite-Width Bayesian Neural Networks Jiayu Yao Yaniv Yacoby Beau Coker Weiwei Pan Finale Doshi-Velez 11 0 0 16 Nov 2022
GFlowOut: Dropout with Generative Flow Networks Dianbo Liu Moksh Jain Bonaventure F. P. Dossou Qianli Shen Salem Lahlou ... Dinghuai Zhang N. Hassen Xu Ji Kenji Kawaguchi Yoshua Bengio UQCV BDL OOD 12 20 0 24 Oct 2022
Monotonicity and Double Descent in Uncertainty Estimation with Gaussian Processes Liam Hodgkinson Christopher van der Heide Fred Roosta Michael W. Mahoney UQCV 8 5 0 14 Oct 2022
Meta-Uncertainty in Bayesian Model Comparison Marvin Schmitt Stefan T. Radev Paul-Christian Burkner UD 11 9 0 13 Oct 2022
Gaussian Process Surrogate Models for Neural Networks Michael Y. Li Erin Grant Thomas L. Griffiths BDL SyDa 15 6 0 11 Aug 2022
Cold Posteriors through PAC-Bayes Konstantinos Pitas Julyan Arbel 13 5 0 22 Jun 2022
Understanding Deep Learning via Decision Boundary Shiye Lei Fengxiang He Yancheng Yuan Dacheng Tao 17 13 0 03 Jun 2022
Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks Agustinus Kristiadi Runa Eschenhagen Philipp Hennig BDL 19 12 0 20 May 2022
Marginal and Joint Cross-Entropies & Predictives for Online Bayesian Inference, Active Learning, and Active Sampling Andreas Kirsch Jannik Kossen Y. Gal UQCV BDL 26 3 0 18 May 2022
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks Marvin Schmitt Paul-Christian Burkner Ullrich Kothe Stefan T. Radev 22 34 0 16 Dec 2021
PAC $^m$ -Bayes: Narrowing the Empirical Risk Gap in the Misspecified Bayesian Regime Warren Morningstar Alexander A. Alemi Joshua V. Dillon 71 16 0 19 Oct 2020
Pac-Bayesian Supervised Classification: The Thermodynamics of Statistical Learning O. Catoni 130 451 0 03 Dec 2007