Bayesian Approach

Bayesian approaches offer a powerful framework for incorporating uncertainty into various machine learning tasks, aiming to improve model robustness, interpretability, and reliability. Current research focuses on applying Bayesian methods to diverse areas, including clustering, regression (especially for circular data and PDEs), and reinforcement learning, often employing techniques like Thompson sampling, Markov Chain Monte Carlo, and variational inference within models such as Bayesian neural networks and Gaussian processes. This focus on uncertainty quantification and robust inference has significant implications for numerous fields, enhancing the trustworthiness of predictions in applications ranging from audio recognition and traffic prediction to structural health monitoring and public health interventions.

Papers

February 7, 2024

A Bayesian Approach to Online Learning for Contextual Restless Bandits with Applications to Public Health
Biyonka Liang, Lily Xu, Aparna Taneja, Milind Tambe, Lucas Janson
Financial Application Online Learning Online Reinforcement Learning Bayesian Approach Bayesian Learning Restless Multi Armed Bandit Restless Bandit Guideline Adherence Adherence Prediction

February 5, 2024

The last Dance : Robust backdoor attack via diffusion models and bayesian approach
Orson Mengara
Neural Network Diffusion Model Generative Model Backdoor Attack Bayesian Approach Diffusion Sampling Audio Transformer Robust Backdoor Attack Last Straw

February 4, 2024

Variational DAG Estimation via State Augmentation With Stochastic Permutations
Edwin V. Bonilla, Pantelis Elinas, He Zhao, Maurizio Filippone, Vassili Kitsios, Terry O'Kane
Variational Inference Causal Discovery Bayesian Network Bayesian Approach Directed Acyclic Graph State Augmentation Random Permutation

December 20, 2023

Bayesian Transfer Learning
Piotr M. Suder, Jason Xu, David B. Dunson
Transfer Learning Scientific Inference Statistical Learning Bayesian Approach Bayesian Transfer

December 16, 2023

Identity Curvature Laplace Approximation for Improved Out-of-Distribution Detection
Maksim Zhdanov, Stanislav Dereka, Sergey Kolesnikov
Uncertainty Estimation Bayesian Approach Understanding Out of Distribution Accurate Uncertainty Laplace Approximation

December 1, 2023

A Bayesian approach for prompt optimization in pre-trained language models
Antonio Sabbatella, Andrea Ponti, Antonio Candelieri, Ilaria Giordani, Francesco Archetti
Pre Trained Language Model Style PROMPT Prompt Optimization Bayesian Approach Soft Prompt Tuning Discrete Token Prompt Word Discrete Prompt

November 27, 2023

Bayesian Approach to Linear Bayesian Networks
Seyong Hwang, Kyoungjae Lee, Sunmin Oh, Gunwoong Park
Bayesian Network Bayesian Approach Bayesian Regularization

November 9, 2023

November 8, 2023

Evaluating Uncertainty Quantification approaches for Neural PDEs in scientific applications
Vardhan Dongre, Gurpreet Singh Hora
Uncertainty Quantification Bayesian Approach Numerical Experiment Neural PDE

October 18, 2023

Applications of ML-Based Surrogates in Bayesian Approaches to Inverse Problems
Pelin Ersin, Emma Hayes, Peter Matthews, Paramjyoti Mohapatra, Elisa Negrini, Karl Schulz
Financial Application Inverse Problem Surrogate Model Bayesian Approach Wave Equation Machine Learning Based Surrogate

October 17, 2023

Efficient Online Learning with Offline Datasets for Infinite Horizon MDPs: A Bayesian Approach
Dengwang Tang, Rahul Jain, Botao Hao, Zheng Wen
Optimal Policy Online Learning Efficient Reinforcement Learning Bayesian Approach Cumulative Regret Offline Data Infinite Horizon Prior Dependent

October 9, 2023

Aligning Language Models with Human Preferences via a Bayesian Approach
Jiashuo Wang, Haozhao Wang, Shichao Sun, Wenjie Li
Language Generation Natural Language Generation Human Preference Bayesian Approach

September 28, 2023

A Primer on Bayesian Neural Networks: Review and Debates
Julyan Arbel, Konstantinos Pitas, Mariia Vladimirova, Vincent Fortuin
Narrative Review Bayesian Neural Network Bayesian Inference Bayesian Approach Debate Evaluation BNN Layer

September 15, 2023

A Bayesian Approach to Robust Inverse Reinforcement Learning
Ran Wei, Siliang Zeng, Chenliang Li, Alfredo Garcia, Anthony McDonald, Mingyi Hong
Inverse Reinforcement Learning Bayesian Approach

September 14, 2023

A Bayesian approach to breaking things: efficiently predicting and repairing failure modes via sampling
Charles Dawson, Chuchu Fan
Autonomous System Robot Swarm Good Thing Bayesian Approach Differentiable Simulation Failure Analysis Failure Mode

August 28, 2023

Bayesian artificial brain with ChatGPT
Renato A. Krohling
Language Model ChatGPT Generated Conversation Bayesian Approach Inference Problem Bayesian Brain

July 12, 2023

A Bayesian approach to quantifying uncertainties and improving generalizability in traffic prediction models
Agnimitra Sengupta, Sudeepta Mondal, Adway Das, S. Ilgin Guler
Deep Learning Stronger Generalizability Traffic Prediction Traffic Data Bayesian Approach High Uncertainty Value

July 1, 2023

Applied Bayesian Structural Health Monitoring: inclinometer data anomaly detection and forecasting
David K. E. Green, Adam Jaspan
State of the Art Forecasting Bayesian Approach Structural Health Monitoring Inclinometer Data

June 15, 2023

A Bayesian approach to uncertainty in word embedding bias estimation
Alicja Dobrzeniecka, Rafal Urbaniak
Absolute Stance Bias High Uncertainty Anticipation Word Embeddings Bayesian Approach Real Text Word Single Number Metric