Conference Days

• Satellite Workshop Day 1
  16 June 2025
• Satellite Workshop Day 2
  17 June 2025
• Conference Day 1
  18 June 2025
• Conference Day 2
  19 June 2025
• Conference Day 3
  20 June 2025

May subject to changes without prior notice

• Satellite Workshop Day 1 - 16 June 2025
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 08:00am - 09:00am Registration & Networking
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 08:00am - 11:15am Registration & Networking
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 09:00am – 9:45am Robust and Conjugate Gaussian Process Regression Matias Altamirano, University College London,
  UNITED KINGDOM
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 09:45am – 10:30am Misspecification in Gaussian Process Regression Assc Prof. Aretha Teckentrup, University of Edinburgh,
  UNITED KINGDOM
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 10:30am – 11:00am Break
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 11:00am – 11:45am Model Misspecification in Martingale Posteriors Asst Prof. Edwin Fong, University of Hong Kong,
  HONG KONG SAR, CHINA
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 11:15am – 11:45am Welcome & Opening Address Prof. Nadja Klein, Karlsruhe Institute of Technology,
  GERMANY Dr. Lucas Kock, National University of Singapore,
  SINGAPORE
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 11:45am – 12:30pm Deep Distributional Time Series Models and the Probabilistic Forecasting of Intraday Electricity Prices Prof. Michael Stanley Smith, University of Melbourne,
  AUSTRALIA
  12:30pm – 02:00pm Lunch
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 02:00pm – 03:30pm
  Generalisation Analysis for Active Learning Under Model Misspecification Roubing Tang, University of Manchester,
  UNITED KINGDOM
  A Principled Approach to Bayesian Transfer Learning Adam Bretheron, Queesnland University of Technology,
  AUSTRALIA
  Predictive Performance of Power Posteriors Yann McLatchie, University College London,
  UNITED KINGDOM
  A Unifying Framework for Generalised Bayesian Online Learning in Non-stationary Environments Gerardo Duran-Martin, Queen Mary University,
  UNITED KINGDOM
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 02:00pm – 02:45pm Varying-coefficients Bayesian models for Inference of Networks and Covariate Effects Prof. Marina Vannucci, Rice University,
  UNITED STATES OF AMERICA
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 02:45pm – 03:30pm Towards Flexibility and Efficiency of Gaussian Process State-Space Models Dr. Zhidi Lin, National University of Singapore,
  SINGAPORE
  03:30pm – 04:00pm Break
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 04:00pm – 05:00pm Likelihood Distortion and Bayesian Local Robustness Prof. Antonietta Mira, Università Della Svizzera Italiana
  ITALY
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 04:00pm – 05:00pm ProDAG: Projection-Induced Variational Inference for Directed Acyclic Graphs Prof. Robert Kohn, University of New South Wales,
  AUSTRALIA
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 05:00pm – 06:00pm Adaptive Nonparametric Perturbations of Parametric Bayesian Models Dr. Eli Weinstein, Columbia University,
  UNITED STATES OF AMERICA
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 04:45pm – 06:00pm Copula-based Models for Spatially Dependent Cylindrical Data Francesca Labanca, University of Florence,
  ITALY
• Satellite Workshop Day 2 - 17 June 2025
  08:00am – 09:00am Registration & Networking
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 09:00am – 10:30am Post-Bayesian Inference Assc. Prof. Jeremias Knoblauch, University College London,
  UNITED KINGDOM
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 09:00am – 09:45am Radial Neighbours for Provably Accurate Scalable Approximations of Gaussian Processes Assc Prof. Cheng Li, National University of Singapore,
  SINGAPORE
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 09:45am - 10:30am Bayesian Structural Learning: Applications in Biological Systems Prof. Maria De Lorio, National University of Singapore,
  SINGAPORE
  10:30am – 11:00am Break
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 11:00am – 11:45am Resampling within MCMC: Approaches, Computational Benefits, and Statistical Properties Asst. Prof. Jonathan Huggins, Boston University,
  UNITED STATES OF AMERICA
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 11:00am – 11:45am Time-varying Multi-seasonal ARMA Processes with Semiparametric Evolution Over Time Prof. Mattias Villani, Stockholm University,
  SWEDEN
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 11:45am - 12:30pm Model-based Distributionally Robust Optimisation: Bayesian Ambiguity Sets and Model Misspecification Dr. Harita Dellaporta, University College London,
  UNITED KINGDOM
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 11:45am - 12:30pm Monte Carlo Inference for Semiparametric Bayesian Regression Dr. Bohan Wu, Columbia University,
  UNITED STATES OF AMERICA
  12:30pm – 02:00pm Lunch
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 02:00pm – 03:30pm
  Multi-scale Uncertainties in Fracture Conductivity for CO2 Storage under Model Misspecification Dr. Sarah Perez, Heriot-Watt University,
  UNITED KINGDOM
  Robust Simulation-based Inference under Missing Data Dr. Ayush Bharti, Aalto University,
  FINLAND
  Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan Kelly, Queensland University of Technology,
  AUSTRALIA
  Prediction-centric Uncertainty Quantification via MMD Prof. Chris Oates, Newcastle University,
  UNITED KINGDOM
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 02:00pm - 02:45pm Semi-Parametric Local Variable Selection under Misspecification Prof. David Rossell, Pompeu Fabra University,
  SPAIN
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 02:45pm - 03:30pm Bayesian Function-on-Function Regression for Spatial Functional Data Asst. Prof. Jaewoo Park, Yonsei University,
  SOUTH KOREA
  03:30pm – 04:00pm Break
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 04:00pm – 05:00pm A New Mutual Information Bound for Statistical Inference Prof. Pierre Alquier, ESSEC Business School,
  FRANCE
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 04:00pm - 05:00pm Regression with Random Rectangle Summaries and Variational Transdimensional Inference Prof. Scott A. Sisson, University of New South Wales,
  AUSTRALIA
  Satellite Workshop 1:
  Bayesian Computation and Inference with Misspecified Models Auditorium 2 05:00pm - 06:00pm Data-centric Semi-modular Bayesian Inference Prof. David T. Frazier, Monash University,
  AUSTRALIA
  Satellite Workshop 2:
  Bayesian Methods for Distributional and Semiparametric Regression LT50 05:00pm - 06:00pm Orthogonal Calibration via Posterior Projections with Applications to the Schwarzschild Model Asst. Prof. Antik Chakraborty, Purdue University,
  UNITED STATES OF AMERICA
• Conference Day 1 - 18 June 2025
  Auditorium 2 08:00am – 09:00am Registration & Networking
  Auditorium 2 09:00am - 09:10am Welcome & Opening Address Prof. David T. Frazier, Monash University,
  AUSTRALIA Assc Prof. David Nott, National University of Singapore,
  SINGAPORE
  Keynote 1 Auditorium 2 09:10am – 10:00am Some progress on unbiased MCMC Prof. Pierre E. Jacob, ESSEC Business School,
  FRANCE Chair:
  Prof. Chris Oates, Newcastle University,
  UNITED KINGDOM
  Auditorium 2 10:10am – 10:30am Break
  Parallel Invited Sessions Advances in Efficient Bayesian Inference for Complex Multivariate Models Auditorium 2 10:30am – 12:00pm Organiser and Chair:
  Dr. Linda Tan Siew Li, National University of Singapore,
  SINGAPORE

  
  Bayesian Regularized Regression Copula Processes for Multivariate Responses Prof. Nadja Klein, Karlsruhe Institute of Technology,
  GERMANY
  Variational Approximate Inference in Structural Equation Modeling Dr Luca Maestrini, Australian National University,
  AUSTRALIA
  A Generalized Functional Delta Method with Applications to Bayesian Inference Assc Prof. Hien Nguyen, La Trobe University,
  AUSTRALIA
  Parallel Invited Sessions (Almost) Gradient-based Markov chain Monte Carlo Algorithms LT50 10:30am – 12:00pm Organiser and Chair:
  Dr. Dootika Vats, Indian Institute of Technology Kanpur,
  INDIA

  
  Proximal Interacting Particle Langevin Algorithms Asst Prof. Francesca Romana Crucinio, King’s College London,
  UNITED KINGDOM
  Stereographic Multi-Try Metropolis Algorithms for Heavy-tailed Sampling Zhihao Wang, University of Copenhagen,
  DENMARK
  Repelling-Attracting Hamiltonian Monte Carlo for High Dimensional Multimodality Asst Prof. Siddharth Vishwanath, University of California,
  UNITED STATES OF AMERICA
  Parallel Invited Sessions Scalable Causal Inference LT51 10:30am – 12:00pm Organiser and Chair:
  Prof. Maria De Iorio, National University of Singapore,
  SINGAPORE

  
  Inference for Enriched Dirichlet Process Mixtures for Large n and a Rare Outcome with Missingness Prof. Michael J. Daniels, University of Florida,
  UNITED STATES OF AMERICA
  Fast Machine Learning Causal Network Analysis Using Genetic Instruments Hui Guo, University of Manchester,
  UNITED KINGDOM
  Efficient Sampling for Bayesian Networks and Benchmarking Their Structure Learning Dr. Jack Kuipers, ETH Zürich,
  SWITZERLAND
  Parallel Invited Sessions Comparison Theory for Modern MCMC Methods Global Learning Room 10:30am – 12:00pm Organiser and Chair:
  Dr. Andi Q. Wang, University of Warwick,
  UNITED KINGDOM

  
  Analysis of Multiple-try Metropolis via Poincaré Inequalities Rocco Caprio, University of Warwick,
  UNITED KINGDOM
  Spectral Gap Bounds for Reversible Hybrid Gibbs Chains Dr. Guangyang Wang, University of Minnesota,
  UNITED STATES OF AMERICA
  Gradient-free Parallel Sampling Prof. Giacomo Zanella, Bocconi University,
  ITALY
  12:00pm – 01:45pm Lunch
  Parallel Invited Sessions Advances in Efficient Bayesian Inference for Complex Multivariate Models Auditorium 2 01:45pm – 03:00pm Organiser and Chair:
  Prof. Maria De Iorio, National University of Singapore,
  SINGAPORE

  
  Graph of Graphs: From Nodes to Supernodes in Graphical Models Prof. Alexandros Beskos, University College London,
  UNITED KINGDOM
  ABC for Network Models via a Multi-scale Summary Statistic Prof. Antonietta Mira, Università della Svizzera italiana,
  SWITZERLAND
  Bayesian Structural Learning with Parametric Marginals for Count Data: An Application to Microbiota Systems Dr. Pariya Behrouzi, Wageningen University and Research,
  THE NETHERLANDS
  Parallel Invited Sessions Bayesian Computation in Astrophysics LT50 01:45pm – 03:00pm Organiser and Chair:
  Dr. Kate Lee, University of Auckland,
  NEW ZEALAND

  
  Accelerating Bayesian Inference on Populations of Merging Binary Black Hole via Active Learning Dr. Avi Vajpeyi, University of Auckland,
  NEW ZEALAND
  Novel Sampling Algorithms for Posterior Estimation in the Physical Sciences Asst Prof Alvin Chua, National University of Singapore,
  SINGAPORE
  Bayesian Parameter Estimation and Model Selection Problems in Astrophysics Asst Prof Joshua S. Speagle, University of Toronto,
  CANADA
  Parallel Invited Sessions Manifold Markov Chain Monte Carlo and Beyond LT51 01:45pm – 03:00pm Organiser and Chair:
  Prof. Daniel Rudolf, University of Passau,
  GERMANY

  
  Geodesic Slice Sampling on Riemannian Manifolds Dr. Mareike Hasenpflug, University of Passau,
  GERMANY
  Adaptive Stereographic MCMC Cameron Bell, University of Warwick,
  UNITED KINGDOM
  Dimension-independent Markov Chain Monte Carlo on the Sphere Dr. Björn Sprungk, TU Bergakademie Freiberg,
  GERMANY
  Parallel Invited Sessions Model Misspecification in Simulation-based Inference Global Learning Room 01:45pm – 03:00pm Organiser and Chair:
  Dr. Ayush Bharti, Aalto University,
  FINLAND

  
  Multi-level Neural Simulation-based Inference Assc Prof. Francois-Xavier Briol, University College London,
  UNITED KINGDOM
  Robust Amortized Bayesian Inference with Self-Consistency Losses on Unlabeled Data Prof. Paul-Christian Bürkner, TU Dortmund University,
  GERMANY
  Addressing Misspecification in Simulation-based Inference through Data-driven Calibration Dr. Antoine Wehenkel, Apple Inc.,
  SWITZERLAND
  03:10pm – 03:30pm Break
  Parallel Contributed Sessions Approximate Inference Methods Auditorium 2 03:30pm – 05:30pm

  
  An Adaptive Approximate Bayesian Computation MCMC with Global-Local Proposals Asst Prof. Shijia Wang, ShanghaiTech University,
  CHINA
  Preconditioned Neural Posterior Estimation for Likelihood-free Inference Prof. Chirstopher Drovandi, Queensland University of Technology,
  AUSTRALIA
  Efficient Tuning of Multifidelity Simulation-based Inference for Computationally Expensive Simulators Dr David J. Warne, Queensland University of Technology,
  AUSTRALIA
  Martingale Correction for Mean Field Variational Inference Laura Battaglia, University of Oxford,
  UNITED KINGDOM
  Divide-and-conquer SMC for Integrating Bayesian models using Markov Melding Dr Yixuan Liu, University of Cambridge,
  UNITED KINGDOM
  A Closed-Form Transition Density Expansion for Elliptic and Hypo-Elliptic SDEs Yuga Iguchi, University College London,
  UNITED KINGDOM
  Parallel Contributed Sessions Modular Inference, Predictive Inference and Sparsity LT50 03:30pm – 05:30pm

  
  New (and Old) Predictive Schemes with “a.c.i.d.” Sequences Asst Prof. Lorenzo Cappello, Universitat Pompeu Fabra,
  SPAIN
  Validating uncertainty propagation approaches for two-stage Bayesian spatial models using simulation-based calibration Stephen Jun Villejo, University of Glasgow,
  UNITED KINGDOM University of the Philippines,
  PHILIPPINES
  A General Framework for Cutting Feedback in Bayesian Models Dr. Robert Goudie, University of Cambridge,
  UNITED KINGDOM
  Bayesian Nonparametric Hypothesis Testing Methods on Multiple Comparisons Asst Prof. Zhuanzhuan Ma, The University of Texas Rio Grande Valley,
  UNITED STATES OF AMERICA
  A Bayesian Regression for Directional Responses Assc Prof. Subhadip Pal, UAE University,
  UNITED ARAB EMIRATES
  Group Penalised Credible Region for Bayesian Variable Selection Khue-Dung Dang, The University of Western Australia,
  AUSTRALIA
  Parallel Contributed Sessions Complex Modelling and Computation LT51 03:30pm – 05:30pm

  
  Exact Sampling of Gibbs Measures with Estimated Losses Dr Jack Jewson, Monash University,
  AUSTRALIA
  Gaussian Process Surrogates for Bayesian Inverse Problems Asst Prof Jonathan Huggins, Boston University,
  UNITED STATES OF AMERICA
  Saddlepoint Monte Carlo and its Application to Exact Ecological Inference Dr Robin Ryder, Imperial College London,
  UNITED KINGDOM
  Stochastic Volatility with Informative Missingness Asst Prof Gehui Zhang, Southwest Petroleum University,
  CHINA University of Pittsburgh,
  UNITED STATES OF AMERICA
  Fast Marginal Likelihood Inference for Fitting Stochastic Epidemic Models Assc. Prof. Jason Xu, UCLA,
  UNITED STATES OF AMERICA
  SBAMDT: Bayesian Additive Decision Trees with Adaptive Soft Semi-multivariate Split Rules Huiyan Sang, Texas A&M University,
  UNITED STATES OF AMERICA
  Parallel Contributed Sessions Advanced Monte Carlo Methods Global Learning Room 03:30pm – 05:30pm

  
  An Invitation to Adaptive MCMC Convergence Theory Prof Matti Vihola, University of Jyväskylä,
  FINLAND
  Sequential Exchange Monte Carlo: Sampling Method for Multimodal Distribution without Parameter Tuning Tomohiro Nabika, University of Tokyo,
  JAPAN
  Bayesian Posterior Sampling with Adaptive SMC for Efficient Exploration in Reinforcement Learning Jiaqi Guo, University of Cambridge,
  UNITED KINGDOM
  Sequential Gaussian Processes for Online Learning of Nonstationary Functions Asst Prof Michael Zhang, The University of Hong Kong,
  HONG KONG SAR, CHINA
  Guided Particle Filters for Continuous-time Processes Prof Frank van der Meulen, Vrije Universiteit Amsterdam,
  THE NETHERLANDS
  Sampling with Time-changed Markov Processes Dr Giorgos Vasdekis, Newcastle University,
  UNITED KINGDOM
  Auditorium 2 & LT50 05:30pm – 07:30pm Poster Session & Light Dinner
• Conference Day 2 - 19 June 2025
  Auditorium 2 08:00am – 09:00am Registration & Networking
  Keynote 2 Auditorium 2 09:100am – 10:00am A Dynamic Horseshoe Process Prior and Beyond Organiser:
  Prof. Christian Robert, Université Paris Dauphine,
  FRANCE University of Warwick,
  UNITED KINGDOM
  Auditorium 2 10:00am – 10:20am Break
  Parallel Invited Sessions High-dimensional Discrete Model Search Auditorium 2 10:20am – 11:50am Organiser and Chair:
  Prof. David Rossell, Pompeu Fabra University,
  SPAIN

  
  Zero-order Parallel Sampling Francesco Pozza, Bocconi University,
  ITALY
  Convergence Analysis of Markov Chain Monte Carlo Methods for Model Selection Problems Hyunwoong Chang, University of Texas at Dallas,
  UNITED STATES OF AMERICA
  Bayesian Computation for High-dimensional Gaussian Graphical Models with Spike-and-slab Prior Prof. Déborah Sulem, Universitá de la Svizzera Italiana,
  SWITZERLAND
  Parallel Invited Sessions Advances in Variational Inference LT50 10:20am – 11:50am Organiser and Chair:
  Prof. Randal Douc, Telecom SudParis,
  FRANCE

  
  Near-Optimal Approximations for Bayesian Inference in Function Space Assc Prof. Jeremias Knoblauch, University College London,
  UNITED KINGDOM
  Learning Symmetries with Variational Inference Dr. Charles Margossian, Flatiron Institute,
  UNITED STATES OF AMERICA
  Learning with Importance Weighted Variational Inference Asst Prof. Kamélia Daudel, ESSEC Business School,
  FRANCE
  Parallel Invited Sessions Advanced Langevin Methods for Bayesian Sampling LT51 10:20am – 11:50am Organiser and Chair:
  Dr. Neil K. Chada, City University of Hong Kong,
  HONG KONG SAR, CHINA

  
  Gradient Flows for Statistical Computation - Trends and Trajectories Dr Sam Power, University of Bristol,
  UNITED KINGDOM
  Explicit Convergence Rates of Underdamped Langevin Dynamics under weighted and Weak Poincaré–Lions Inequalities Dr Andi Wang, University of Warwick,
  UNITED KINGDOM
  Explicit Convergence Rates of Underdamped Langevin Dynamics under weighted and Weak Poincaré–Lions Inequalities Dr Peter Whalley, ETH Zürich,
  SWITZERLAND
  Parallel Invited Sessions Computation-enabled Bayesian Inference and Prediction Global Learning Room 10:20am – 11:50am Organiser:
  Prof. Li Ma, Duke University,
  UNITED STATES OF AMERICA Chair:
  Prof. David Frazier, Monash University,
  AUSTRALIA

  
  Predictive Resampling for Scalable Bayes Asst Prof. Edwin Fong, University of Hong Kong,
  HONG KONG SAR, CHINA
  Lessons on Mixing for Bayesian Additive Regression Trees Asst Prof. Yan Shuo Tan, National University of Singapore,
  SINGAPORE
  Tree Boosting for Learning Density Ratios with Generalized Bayesian uUcertainty Quantification Asst Prof. Naoki Awaya, Waseda University,
  JAPAN
  11:50am – 01:40pm Lunch
  Panel Discussion Bayesian Inference and Machine Learning: A Two-way Street Auditorium 2 01:40pm – 03:10pm Moderator:
  Assc Prof. Jeremias Knoblauch, University College London,
  UNITED KINGDOM Prof. Sylvia Fruhwirth-Schnatter, WU Vienna University of Economics and Business,
  AUSTRIA Prof. Pierre E. Jacob, ESSEC Business School,
  FRANCE Prof. Mohammad Emtiyaz Khan, RIKEN Center for Advanced Intelligence Project,
  JAPAN
  03:10pm – 03:30pm Break
  Parallel Invited Sessions Simulation-based Bayesian Inference: Efficiency, Robustness, and Theoretical Results Auditorium 2 03:30pm – 05:30pm Organiser and Chair:
  Prof. Christopher Drovandi, Queensland University of Technology,
  AUSTRALIA

  
  The Statistical Accuracy of Neural Posterior and Likelihood Estimation Prof. David T. Frazier, Monash University,
  AUSTRALIA
  Scalable SBI via Optimization-based Acceleration Asst Prof. Yuexi Wang, University of Illinois Urbana-Champaign,
  UNITED STATES OF AMERICA
  Misspecification-robust Methods for SBI with Neural Conditional Density Estimators Ryan Kelly, Queensland University of Technology,
  AUSTRALIA
  Discussant:
  Assc. Prof. Clara Grazian, University of Sydney,
  AUSTRALIA
  Parallel Invited Sessions Recalibration Methods for Improved Bayesian Inference from Approximate Models LT50 03:30pm – 05:30pm Organiser and Chair:
  Dr. Joshua Bon, Université Paris Dauphine,
  FRANCE

  
  Calibrating/Recalibrating Approximate Bayesian Credible Sets Dr Jeong E (Kate) Lee, University of Auckland,
  NEW ZEALAND
  Model-Free Local Recalibration of Neural Networks Dr Guilherme Souza Rodrigues, University of Brasilia,
  BRAZIL
  Flexible Transformations for Bayesian Score Calibration Adam Bretherton, Queensland University of Technology,
  AUSTRALIA
  Discussant:
  Prof Scott Sisson, University of New South Wales,
  AUSTRALIA
  Parallel Invited Sessions Cutting Feedback: Methods and Applications in Bayesian Settings LT51 03:30pm – 05:30pm Organiser:
  Dr. Anne Presanis, MRC Biostatistics Unit, University of Cambridge,
  UNITED KINGDOM Chair:
  Daniela De Angelis, MRC Biostatistics Unit, University of Cambridge,
  UNITED KINGDOM

  
  Asymptotics of Cut Posteriors and Robust Modular Inference Asst Prof. Mikolaj Kasprzak, ESSEC Business School,
  FRANCE
  Cutting Feedback and Modularized Analyses in Generalized Bayesian Inference Assc Prof. David Nott, National University of Singapore,
  SINGAPORE
  On the Use of Cut-posteriors for Causal Factor Analysis Pantelis Samartsidis, University of Cambridge,
  UNITED KINGDOM
  Discussant:
  Prof Daniela De Angelis, MRC Biostatistics Unit, University of Cambridge,
  UNITED KINGDOM
  Parallel Invited Sessions PDMPs in Practice Global Learning Room 03:30pm – 05:30pm Organiser:
  Luke Harcastle, University College London,
  UNITED KINGDOM Chair:
  Dr. Sebastiano Grazzi, Bocconi University,
  ITALY

  
  Automated Techniques for Efficient Sampling of Piecewise-Deterministic Markov Processes Prof. Kengo Kamatani, The Institute of Statistical Mathematics,
  JAPAN
  Sampling Diffusion Piecewise Exponential Models using Piecewise Deterministic Markov Processes Luke Hardcastle, University College London,
  UNITED KINGDOM
  Zig-zag Sampling for Discrete Variables in Phylogenetics Dr Jere Koskela, University of Newcastle,
  UNITED KINGDOM
  Discussant:
  Dr. Sebastiano Grazzi, Bocconi University,
  ITALY
  Auditorium 2 & LT50 05:30pm – 07:30pm Poster Session & Light Dinner
• Conference Day 3 - 20 June 2025
  Auditorium 2 08:00am – 09:00am Registration & Networking
  Keynote 3 Auditorium 2 09:00am – 10:00am Adaptive Bayesian Intelligence Prof. Mohammad Emtiyaz Khan, RIKEN Center for Advanced Intelligence Project,
  JAPAN Chair:
  Prof. David T. Frazier, Monash University,
  AUSTRALIA
  Auditorium 2 10:00am – 10:20am Break
  Parallel Invited Sessions Bayesian Federated Learning Auditorium 2 10:20am – 11:50am Organiser:
  Prof. Christian Robert, Université Paris Dauphine,
  FRANCE University of Warwick,
  UNITED KINGDOM

  
  Confidential Accept-Reject Assc Prof. Louis J.M. Aslett, Durham University,
  UNITED KINGDOM
  Breaking Dependencies to enable Federated Learning of Bayesian Models Dr Conor Hassan, Aalto University,
  FINLAND
  Likelihood-free Bayesian Model Selection via Sequential Neural Likelihood Estimation Prof. Jean-Michel Marin, Université de Montpellier,
  FRANCE
  Parallel Invited Sessions Flexible Approximate Inference Methods LT50 10:20am – 11:50am Organiser and Chair:
  Assc Prof. David Nott, National University of Singapore,
  SINGAPORE

  
  Weighted Fisher Divergence for High-dimensional Gaussian Variational Inference Dr Linda Tan, National University of Singapore,
  SINGAPORE
  High-Dimensional Multivariate Stochastic Volatility Model Based on A Copula of A Mixture Prof. Robert Kohn, University of New South Wales,
  AUSTRALIA
  Applying Multi-objective Bayesian Optimization to Likelihood-free Inference David Chen National University of Singapore,
  SINGAPORE
  Parallel Invited Sessions Advances in Methodology for Sequential Monte Carlo in High Dimensions LT51 10:20am – 11:50am Organiser and Chair:
  Prof. Alexandros Beskos, University College London,
  UNITED KINGDOM

  
  Mixing Time of the Conditional Backward Sampling Particle Filter Prof. Sumeetpal Singh, University of Wollongong,
  AUSTRALIA
  Particle-MALA and Particle-mGRAD: Gradient-based MCMC Methods for High-dimensional State-space Models Assc Prof. Axel Finke, Newcastle University,
  UNITED KINGDOM
  Sequential Monte Carlo from a Multiple Importance Sampling Perspective Prof. Victor Elvira, University of Edinburgh,
  UNITED KINGDOM
  Parallel Contributed Sessions Computationally Efficient Bayesian Inference Global Learning Room 10:20am – 11:50am

  
  Cost-aware Simulation-based Inference Dr. Ayush Bharti, Aalto University,
  FINLAND
  Probabilistic Richardson Extrapolation Prof. Chris. J. Oates, Newcastle University,
  UNITED KINGDOM
  Extrapolation and Smoothing of Tempered Posteriors Dr. Marina Riabiz, King's College London,
  UNITED KINGDOM
  11:50am – 01:10pm Lunch
  Parallel Invited Sessions Recent advances in Sequential Monte Carlo methods Auditorium 2 01:10pm – 02:40pm Organiser and Chair:
  Dr. Hai-Dang Dau, National University of Singapore,
  SINGAPORE

  
  On the Stability of Schrödinger Bridges and Sinkhorn Semigroups Prof. Pierre Del Moral, NRIA Bordeaux,
  FRANCE
  A Random-walk in the Land of Denoising Diffusions Dr. Adrien Corenflos, University of Warwick,
  UNITED KINGDOM
  Scalable Bayesian Inference for Large Language Model Analysis Asst. Prof Ning Ning, Texas A&M University,
  UNITED STATES OF AMERICA
  Parallel Invited Sessions Computation and model criticism for highly parametrized Bayesian models LT50 01:10pm – 02:40pm Organiser and Chair:
  Assc Prof. David Nott, National University of Singapore,
  SINGAPORE

  
  Latent Random Partition Models: An Application to Childhood Co-morbidity Prof. Maria De Lorio, National University of Singapore,
  SINGAPORE
  Truly Multivariate Structured Additive Distributional Regression Dr. Lucas Kock, National University of Singapore,
  SINGAPORE
  Cutting Feedback in Misspecified Copula Models Prof. Michael Stanley Smith, University of Melbourne,
  AUSTRALIA
  Parallel Invited Sessions Approximate Methods for Accelerated Sampling LT51 01:10pm – 02:40pm Organiser and Chair:
  Asst. Prof. Yuexi Wang, University of Illinois Urbana-Champaign,
  UNITED STATES OF AMERICA

  
  Learning Summary Statistics for Likelihood-free Bayesian Inference Asst Prof. Rong Tang, Hong Kong University of Science and Technology,
  HONG KONG SAR, CHINA
  Explicit Convergence Rates of Underdamped Langevin Dynamics Under Weighted and Weak Poincaré–Lions Inequalities Assc Prof. Yun Yang, University of Maryland, College Park,
  UNITED STATES OF AMERICA
  Inverse CDF for All? An Exploration with Chebyshev Polynomial Posterior Approximation Asst. Prof. Leo Duan, University of Florida,
  UNITED STATES OF AMERICA
  Parallel Invited Sessions Optimization and Control for Sampling Global Learning Room 01:10pm – 02:40pm Organiser and Chair:
  Assc. Prof. Alexandre Thiery, National University of Singapore,
  SINGAPORE

  
  A Dynamical Systems Perspective on Measure Transport and Generative Modeling Dr. Lorenz Richter, Zuse Institute Berlin,
  GERMANY
  Transport meets Variational Inference: Controlled Monte Carlo Diffusions Dr. Nikolas Nüsken, King's College London,
  UNITED KINGDOM
  Stochastic Control for Black-box Inference: Insights from Deep Reinforcement Learning Dr. Nikolay Malkin, University of Edinburgh,
  UNITED KINGDOM
  02:4pm – 03:00pm Break
  Parallel Invited Sessions Surrogate Models and Kernel Methods Auditorium 2 03:00pm – 04:30pm Organiser and Chair:
  Prof. Chris. J. Oates, Newcastle University,
  UNITED KINGDOM

  
  Squared Neural Probabilistic Models Prof. Dino Sejdinovic, University of Adelaide,
  AUSTRALIA
  Fast and Scalable Sequential Experimental Design via Subspace-Accelerated Transport Map Surrogates Dr. Karina Koval, Heidelberg University,
  GERMANY
  High-dimensional Kernel Approximation with Length-scale Informed Sparse Grids Assc Prof. Aretha Teckentrup, University of Edinburgh,
  UNITED KINGDOM
  Parallel Invited Sessions Advances in Heavy-Tailed Sampling: Bridging Theory and Practice LT50 03:00pm – 04:30pm Organiser:
  Dr. Alex Shestopaloff, Queen Mary University of London,
  UNITED KINGDOM

  
  Rapid Mixing of Stereographic MCMC for Heavy-tailed Sampling Federica Milinanni, KTH Royal Institute of Technology,
  SWEDEN
  Stereographic Barker's MCMC Proposal: Efficiency and Robustness at Your Disposal Asst. Prof. Jun Yang, University of Copenhagen,
  DENMARK
  Characterization and Control of Global Dynamics of Heavy-tailed SGD Asst. Prof. Chang-Han Rhee, Northwestern University,
  UNITED STATES OF AMERICA
  Parallel Invited Sessions Variational Bayes for Uncertainty Quantification LT51 03:00pm – 04:30pm Organiser and Chair:
  Asst. Prof. Ryan Giordano, University of California, Berkeley,
  UNITED STATES OF AMERICA Asst. Prof. Alex Strang, University of California, Berkeley,
  UNITED STATES OF AMERICA

  
  Making Variational Inference Work for Statisticians: Parallel Tempering with a Variational Reference Assc Prof. Trevor Campbell, University of British Columbia,
  CANADA
  Batch and Match: Score-based Approaches for Black-box Variational Inference Dr. Diana Cai, Flatiron Institute,
  UNITED STATES OF AMERICA
  Predictive Variational Inference: Learn the Predictively Optimal Posterior Distribution Asst Prof. Yuling Yao, University of Texas at Austin,
  UNITED STATES OF AMERICA
  Parallel Invited Sessions Parallel Computations for Markov Chain Monte Carlo Global Learning Room 03:00pm – 04:30pm Organiser:
  Dr. Sebastiano Grazzi, Bocconi University
  ITALY Chair:
  Dr. Charles Margossian, Flatiron Institute
  UNITED STATES OF AMERICA

  
  Output Analysis for Parallel MCMC Dr. Dootika Vats, Indian Institute of Technology Kanpur
  INDIA
  Parallelized Midpoint Randomization for Langevin Monte Carlo Asst Prof. Lu Yu, City University of Hong Kong
  HONG KONG SAR, CHINA
  Parallel Computations for Metropolis Markov Chains with Picard Maps Dr. Sebastiano Grazzi, Bocconi University
  ITALY
  Auditorium 2 04:30pm Awards and Closing Remarks Prof. David T. Frazier, Monash University,
  AUSTRALIA Assc Prof. David Nott, National University of Singapore,
  SINGAPORE