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Seminar
rm-lewis edited this page Dec 2, 2024
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Join our mailing list by sending a blank email to [email protected].
- Time: Fridays at 16.00-17.00 (time varies on a week-by-week basis, please see below)
- Venue: Small/Large Lecture Theatre (and/or Zoom) at 24 St Giles, Oxford, OX1 3LB.
- Current organisers: Arya Akhavan and Amitis Shidani
- Contact: [email protected]
- Recorded talks: Oxford Statistics Podcasts
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2024.10.18 |
4.00pm | Small Lecture Theatre | Jeremias Knoblauch | Post-Bayesian machine learning |
| 2024.10.25 |
4.00pm | Small Lecture Theatre | Nikola Konstantinov | Incentivizing collaboration in federated learning |
| 2024.11.01 |
4.00pm | Small Lecture Theatre | Nicholas Irons | Causally sound priors for binary experiments |
| 2024.11.08 |
4.00pm | Small Lecture Theatre | Miha Bresar | Non-asymptotic bounds for forward processes in denoising diffusions: Ornstein-Uhlenbeck is hard to beat |
| 2024.11.13 |
11.00pm | Small Lecture Theatre | Nikolas Nusken | Transport meets variational inference: controlled Monte Carlo diffusions |
| 2024.11.22 |
4.00pm | Small Lecture Theatre | Yingzhen Li | Towards causal deep generative models for sequential data |
| 2024.11.29 |
4.00pm | Small Lecture Theatre | Tingting Zhu | From data to decisions: generative models for individualised healthcare |
| 2024.12.06 |
4.00pm | Small Lecture Theatre | Mona Azadkia | A simple measure of conditional dependence |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2024.07.26 |
4.00pm | Small Lecture Theatre | Andrej Risteski | The statistical cost of score-based losses |
| 2024.08.09 |
4.00pm | Small Lecture Theatre | Taeyoung Kim | Transformers can perform distributionally-robust optimisation through in-context learning |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2024.04.10 | 2.00pm | Small Lecture Theatre | Mareike Hasenpflug | Geodesic slice sampling on Riemannian manifolds |
| 2024.04.19 | 2.00pm | Small Lecture Theatre | Umut Simsekli | Implicit compressibility of overparametrized neural networks trained with heavy-tailed SGD |
| 2024.04.25 | 4.00pm | LG.04 | Murat A. Erdogdu | Feature learning in two-layer neural networks: the effect of data covariance |
| 2024.04.26 | 2.00pm | Small Lecture Theatre | Stijn Vansteelandt | Assumption-lean modeling and orthogonal learning conditional average treatment effects |
| 2024.04.30 | 2.00pm | Small Lecture Theatre | Francesca Panero | Modeling sparse networks with Bayesian nonparametrics |
| 2024.05.06 | 2.00pm | Small Lecture Theatre | Claudia Czado | Vine copula-based regression models |
| 2024.05.17 | 2.00pm | Small Lecture Theatre | Florian Pfaff | Recursive Bayesian estimation on periodic manifolds and beyond |
| 2024.05.24 | 2.00pm | Small Lecture Theatre | Zhu (Michael) Li | Nonlinear meta-learning can guarantee faster rates |
| 2024.06.07 | 2.00pm | Small Lecture Theatre | Benjamin Guedj | On generalisation and learning |
| 2024.06.12 | 10.30am | Open Research Zone | Pang Wei Koh | Reliable and responsible data use: retrieval-based models and synthetic data |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2024.01.19 | 2.00pm | Small Lecture Theatre | Rebecca Lewis | High-dimensional logistic regression with separated data |
| 2024.02.02 | 2.00pm | Small Lecture Theatre | Alessandro Barp | What is a distribution? Constructing a geometric backbone for statistical methodologies |
| 2024.02.16 | 2.00pm | Small Lecture Theatre | Laurence Aitchison | Deep kernel processes and machines |
| 2024.02.22 | 2.00pm | Small Lecture Theatre | David Burt | Consistent Validation for Predictive Methods in Spatial Settings |
| 2024.03.01 | 2.00pm | Small Lecture Theatre | Thomas Berrett | Nonparametric tests of Missing Completely At Random |
| 2024.03.08 | 2.00pm | Large Lecture Theatre | Mathieu Gerber | Online parameter and state estimation in state space models |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2023.10.13 | 2.00pm | Small Lecture Theatre | Spencer Frei | Learning linear models in-context with transformers |
| 2023.10.19 | 3.30pm | Large Lecture Theatre | Kerrie Mengersen | Dealing with Sensitive Data |
| 2023.10.20 | 2.00pm | Small Lecture Theatre | O. Deniz Akyildiz | Interacting Particle Langevin Algorithm for Maximum Marginal Likelihood Estimation |
| 2023.10.27 | 2.00pm | Small Lecture Theatre | Georgios Batzolis | Your diffusion model secretly knows the dimension of the data manifold |
| 2023.11.02 | 3.30pm | Large Lecture Theatre | Arno Solin | Structured Inductive Biases in Machine Learning: Approaches to Magnetic SLAM and Multi-scale Generative Modelling |
| 2023.11.03 | 2.00pm | Small Lecture Theatre | Stathi Fotiadis | Accelerating Diffusion Model Sampling: Techniques for Training and Inference |
| 2023.11.10 | 1.00pm | Small Lecture Theatre | Bobby He | Simplifying Transformer Blocks |
| 2023.11.10 | 2.00pm | Small Lecture Theatre | Nicolas Flammarion | Saddle-to-saddle dynamics in diagonal linear networks |
| 2023.11.17 | 2.00pm | Small Lecture Theatre | Laurence Midgley | Flow Annealed Importance Sampling Bootstrap |
| 2023.11.24 | 2.00pm | Small Lecture Theatre | Richard Turner | Neural Processes for Environmental Prediction |
| 2023.12.01 | 2.00pm | Small Lecture Theatre | Antonio Orvieto | Long-range reasoning on graphs without attention |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2023.04.21 | 12.30pm | Large Lecture Theatre | Kaifeng Lyu | Why (and When) does Local SGD Generalize Better than SGD? |
| Abhishek Panigrahi | Task-Specific Skill Localization in Fine-tuned Language Models | |||
| Sadhika Malladi | Modeling SGD with Stochastic Differential Equations: Theory and Applications | |||
| 2023.04.28 | 2pm | Large Lecture Theatre | Aki Nishimura | Zigzag path connects two Monte Carlo paradigms: Hamiltonian counterparts to piecewise deterministic Markov processes |
| 2023.05.05 | 2pm | Small Lecture Theatre | Leonard Henckel | Graphical Tools for Selecting Conditional Instrumental Sets |
| 2023.05.12 | 4pm | Small Lecture Theatre | Paolo Perrone | Probability, symmetry, and entropy with Markov categories |
| 2023.05.19 | 4pm | Small Lecture Theatre | Benedicte Colnet | Risk ratio, odds ratio, risk difference... Which causal measure is easier to generalize? |
| 2023.06.02 | 2pm | Small Lecture Theatre | Ardjen Pengel | Gaussian approximation and variance estimation for high-dimensional MCMC |
| 2023.06.09 | 2pm | Small Lecture Theatre | Louis Sharrock | Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates |
| 2023.06.16 | 1.30pm | Large Lecture Theatre | Jakiw Pidstrigach | Infinite-Dimensional Diffusion Models for Function Spaces |
| 3pm | Brian Trippe | Twisted diffusion sampling for accurate conditional generation with application to protein design | ||
| 4.30pm | Sanjeev Arora | A Theory for Emergence of Complex Skills in Large Language Models | ||
| 2023.06.23 | 2pm | Small Lecture Theatre | Sifan Liu | An Exact Sampler for Inference after Polyhedral Model Selection |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2023.01.20 | 4pm | Large Lecture Theatre | Lauren Kennedy | Using structured priors for survey adjustment |
| 2023.01.27 | (cancelled) | |||
| 2023.02.03 | (Florence Nightingale Lecture) | |||
| 2023.02.10 | 1pm | LG.04 | Viacheslav Borovitskiy | Geometric Gaussian Processes |
| 4pm | Large Lecture Theatre | Sam Power | Explicit convergence bounds for Metropolis Markov chains | |
| 2023.02.17 | 4pm | Jeremias Knoblauch | Optimisation-centric generalisations of Bayesian inference | |
| 2023.02.24 | 4pm | Chengchun Shi | Statistical Inference in Reinforcement Learning | |
| 2023.03.03 | 2pm | Johan van der Molen | Dirichlet process mixture inconsistency for the number of components: how worried should we be in practice? | |
| 4pm | Gergely Neu | Optimistic Planning by Regularized Dynamic Programming | ||
| 2023.03.10 | 4pm | Tui Nolan | Orthogonal Bayesian Functional Principal Components Analysis |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 2022.11.18 | 2:30pm | Large Lecture Theatre | Jakob Foerster | Opponent-Shaping and Interference in General-Sum Games |
| 2022.11.25 | 2:30pm | Large Lecture Theatre | Hongseok Yang | Learning Symmetric Rules with SATNet |
| 2022.12.02 | 2:30pm | Large Lecture Theatre | Francesca Panero | Achieving fairness with a simple ridge penalty |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 15 Apr 2022 | 4:30pm | Zoom | Geoffrey Schiebinger | Towards a mathematical theory of development |
| 29 Apr 2022 | (cancelled) | |||
| 6 May 2022 | 3:30pm | large lecture theatre and Zoom | Siyuan Guo | Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data |
| 13 May 2022 | 3:30pm | Zoom | Xin T. Tong | Can Algorithms Collaborate? The Replica Exchange Method and Its Spectral Gap |
| 20 May 2022 | (Oxford Maths and Stats Colloquium) | |||
| 27 May 2022 | 4pm | small lecture theatre and Zoom | Saifuddin Syed | Non-reversible parallel tempering |
| 3 Jun 2022 | Badr-Eddine Chérief-Abdellatif | |||
| 10 Jun 2022 | (Fridays@4 Maths Meets Stats) | |||
| 22 Jun 2022 | (TBA) | Cecilia Balocchi | Bayesian Nonparametric Analysis of Spatial Variation with Discontinuities | |
| 24 Jun 2022 | Elizaveta Semenova | Encoding spatial priors with VAEs for geospatial modelling |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 21 Jan 2022 | 2pm | large lecture theatre and zoom | Robert Goudie | Joining Bayesian submodels with Markov melding |
| 28 Jan 2022 | 4pm | large lecture theatre and zoom | Anastasia Ignatieva | Genealogy-based inference of recombination |
| 4 Feb 2022 | 4pm | zoom | James Martens | Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping |
| 11 Feb 2022 | 4pm | large lecture theatre and zoom | Agni Orfanoudaki | Machine Learning Algorithms for Personalised Medicine & Insurance |
| 18 Feb 2022 | 4pm | large lecture theatre and zoom | Lionel Riou-Durand | Metropolis Adjusted Underdamped Langevin Trajectories: a robust alternative to Hamiltonian Monte-Carlo |
| 25 Feb 2022 | 4pm | large lecture theatre and zoom | Konstantinos Zygalakis | Connection Between Optimization and Sampling Algorithms |
| 4 Mar 2022 | (Florence Nightingale Lecture) | |||
| 11 Mar 2022 | 4pm | zoom | Guodong Zhang | Training Deep Neural Networks without Shortcuts |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 15 Oct 2021 | 4:00 pm | small lecture theatre and Zoom | Seth Flaxman | Statistical challenges from a pandemic |
| 22 Oct 2021 | (OxWaSP annual workshop) | |||
| 29 Oct 2021 | (cancelled) | |||
| 5 Nov 2021 | 4:00 pm | large lecture theatre and Zoom | Matteo Giordano | Consistent Bayesian nonparametric inference in inverse problems |
| 12 Nov 2021 | 4:00 pm | large lecture theatre and Zoom | Jakob Foerster | Off-Belief Learning and Zero-Shot Coordination |
| 19 Nov 2021 | 4:00 pm | large lecture theatre and Zoom | Kamelia Daudel | Infinite-dimensional Alpha-divergence minimisation for Variational Inference |
| 26 Nov 2021 | 4:00 pm | large lecture theatre and Zoom | Wenkai Xu | Kernel Stein Discrepancies for Goodness-of-fit Testing |
| 3 Dec 2021 | (Corcoran Memorial Prize Award and Lecture) | |||
| 10 Dec 2021 | 4:00 pm | Zoom | Jeffrey Negrea | Statistical Inference with Stochastic Gradient Algorithms |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 23 April 2021 | 3:30 pm | Zoom | Roger Grosse | Self-tuning networks: Amortizing the hypergradient computation for hyperparameter optimization |
| 30 April 2021 | 3:30 pm | Zoom | Julyan Arbel | Approximate Bayesian computation with surrogate posteriors |
| 7 May 2021 | 3:30 pm | Zoom | Aki Vehtari | Practical pre-asymptotic diagnostic of Monte Carlo estimates in Bayesian inference and machine learning |
| 14 May 2021 | 3:30 pm | Zoom | Cynthia Rudin | Do simpler models exists and how can we find them? |
| 21 May 2021 | 3:30 pm | Zoom | James Johndrow | Spectral gaps and error estimates for infinite-dimensional Metropolis-Hastings with non-Gaussian priors |
| 28 May 2021 | 3:30 pm | Zoom | Alexandra Carpentier | Several structured thresholding bandit problems |
| 4 June 2021 | 3:30 pm | Zoom | Qiang Liu | Recent Applications of Stein's Method in Machine Learning |
| 11 June 2021 | 3:30 pm | Zoom | (cancelled) | |
| 18 June 2021 | 3:30 pm | Zoom | Susan Murphy | (Distinguished speaker series) |
| 25 June 2021 | 3:30 pm | Zoom | Quan Zhou | Complexity of local MCMC methods for high-dimensional model selection |
| 2 July 2021 | 3:30 pm | Zoom | Caroline Uhler | Causality and Autoencoders in the Light of Drug Repurposing for COVID-19 |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 15 January 2021 | 3:30 pm | Zoom | Lénaïc Chizat | Faster Wasserstein distance estimation with the Sinkhorn divergence |
| 22 January 2021 | 11:00 am | Zoom | Chris Gamble | DeepMind: AI as a Science and AI for Science |
| 29 January 2021 | 3:30 pm | Zoom | Victor Veitch | Causal Estimation with Machine Learning without (Simple) Unconfoundedness |
| 5 February 2021 | 3:30 pm | Zoom | Sinnead Williamsom | Bayesian nonparametric models for interaction networks |
| 12 February 2021 | 3:30 pm | Zoom | Veronika Rockova | METROPOLIS-HASTINGS VIA CLASSIFICATION |
| 19 February 2021 | 3:30 pm | Zoom | François-Xavier Briol | Kernel-based robust inference for intractable likelihood models |
| 26 February 2021 | 3:30 pm | Zoom | Karolina Dziugaite | Distribution-dependent generalization bounds for noisy, iterative learning algorithms |
| 5 March 2021 | 3:30 pm | Zoom | Linda Siew Li Tan | Use of model reparametrization to improve variational Bayes |
| 12 March 2021 | 3:30 pm | Zoom | Murat A. Erdogdu | Convergence of Online SGD under Infinite Noise Variance, and Non-convexity |
| 19 March 2021 | 3:30 pm | Zoom | Maire Florian | Approximate asymptotic variance ordering for MCMC |
| 26 March 2021 | 3:30 pm | Zoom | Benjamin Guedj | A primer on PAC-Bayesian learning followed by News from the PAC-Bayes frontline |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 24 January 2020 | 3:30 pm | small lecture theatre | Alessandro Barp | Sampling Distributions on Manifolds with Hamiltonian Monte Carlo |
| 13 February 2020 | TBA | TBA | Nicolas Heess | TBA |
| 14 February 2020 | 3:30 pm | small lecture theatre | Michael Arbel | TBA |
| 28 February 2020 | 3:30 pm | small lecture theatre | Danielle Belgrave | TBA |
| 6 March 2020 | 3:30 pm | small lecture theatre | David Pfau | TBA |
| 13 March 2020 | 3:30 pm | small lecture theatre | Benjamin Guedj (cancelled) | A primer on PAC-Bayesian learning, and application to deep neural networks |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 20 September 2019 | 3:30 pm | large lecture theatre | Masashi Sugiyama | Machine Learning from Weak Supervision: Towards Accurate Classification with Low Labeling Costs |
| 7 October 2019 | 3:30 pm | small lecture theatre | Maurizio Filippone | Walsh-Hadamard Variational Inference for Bayesian Deep Learning |
| 11 October 2019 | 3:30 pm | Lecture Theatre B, Wolfson Building, 15 Parks Rd | David Barber | Spread Divergences |
| 18 October 2019 | 3:30 pm | small lecture theatre | Andrew Saxe | Dynamics of generalization error in overparametrized neural networks |
| 24 October 2019 | 3:30 pm | Lecture Theatre B, Wolfson Building, 15 Parks Rd | Bert Kappen | Training a quantum system to represent classical data |
| 25 October 2019 | 11:00 am | small lecture theatre | Jonathan Huggins | Using bagged posteriors for robust inference and model criticism |
| 25 October 2019 | 3:30 pm | small lecture theatre | Martin Wiegel | Population simulation methods for parallel computing |
| 1 November 2019 | 3:30 pm | small lecture theatre | Dino Oglic | On Scalable Learning in Krein Spaces and Cyclic Discovery Processes |
| 15 November 2019 | 3:30 pm | small lecture theatre | Irina Higgins | What is disentangling and does intelligence need it? |
| 29 November 2019 | 11:00 am | large lecture theatre | Takeru Matsuda | Estimation and selection of non-normalized models |
| 6 December 2019 | 3:30 pm | small lecture theatre | Pierre Alquier | A Generalization Bound for Online Variational Inference |
| 13 December 2019 | 3:30 pm | small lecture theatre | Saifuddin Syed | Non-reversible parallel tempering: a scalable, highly parallel MCMC algorithm |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 3 May 2019 | 3:30pm | small lecture theatre | Xiaowen Dong [Oxford] | A maximum-mean-discrepancy goodness-of-fit test for censored data |
| 10 May 2019 | 3:30pm | small lecture theatre | Umut Şimşekli [Télécom ParisTech] | Nonparametric Generative Modeling via Optimal Transport and Diffusions with Provable Guarantees |
| 17 May 2019 | 3:30pm | small lecture theatre | No seminar | Departmental Distinguished Seminar |
| 20 May 2019 | 3:30pm | small lecture theatre | Cédric Févotte [Toulouse] | TBD |
| 24 May 2019 | 3:30pm | small lecture theatre | Chris Sherlock [Lancaster] | Fast, exact inference for discretely observed Markov jump processes using finite rate matrices |
| 30 May 2019 | 3:30pm | large lecture theatre | Ingo Steinwart [Stuttgart] | Neural Networks: Initializations and Global Minima |
| 31 May 2019 | 3:30pm | small lecture theatre | Eric Nalisnick [Cambridge] | Evaluating Deep Generative Models on Out-of-Distribution Inputs |
| 7 June 2019 | 3:30pm | small lecture theatre | Kody Law [Manchester] | Bayesian Static Parameter Estimation for Partially Observed Diffusions using Multilevel Monte Carlo |
| 14 June 2019 | 3:30pm | small lecture theatre | Cancelled due to distinguished seminar | TBD |
| 21 June 2019 | 3:30pm | small lecture theatre | Chris Nemeth [Lancaster] | TBD |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 1 February 2019 | 3:30pm | small lecture theatre | Tamara Fernandez [UCL] | A maximum-mean-discrepancy goodness-of-fit test for censored data |
| 8 February 2019 | 3:30pm | small lecture theatre | Olga Isupova [Oxford] | TBD |
| 15 February 2019 | 3:30pm | small lecture theatre | Lorenzo Rosasco [Genova and MIT] | TBD |
| 22 February 2019 | 3:30pm | small lecture theatre | Richard Wilkinson [Sheffield] | TBD |
| 1 March 2019 | 3:00pm | large lecture theatre | Jose-Miguel Hernandez Lobato [Cambridge] | Advances in machine learning for molecules |
| 8 March 2019 | 3:30pm | small lecture theatre | David Martínez [Oxford] | TBD |
| 15 March 2019 | 3:30pm | small lecture theatre | Shimon Whiteson [Oxford] | TBD |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 05 October 2018 | 3:30pm | large lecture theatre | Song Liu [Bristol] | Model Inference with Stein Density Ratio Estimation |
| 19 October 2018 | 3:30pm | small lecture theatre | Anthony Caterini / Lawrence Middleton [Oxford] | Hamiltonian Variational Auto-Encoder / Parallelising particle MCMC through exact estimation |
| 26 October 2018 | 3:30pm | small lecture theatre | Chris Maddison [Oxford] | Hamiltonian Descent Methods |
| 2 November 2018 | 3:30pm | small lecture theatre | Alexander Lvovsky [Oxford] | Quantum optical Ising machines and their simulators for annealing and machine learning |
| 9 November 2018 | 3:30pm | large lecture theatre | Aapo Hyvarinen [Gatsby] | Nonlinear independent component analysis: A principled framework for unsupervised deep learning |
| 16 November 2018 | 3:30pm | large lecture theatre | Brooks Paige [Turing] | Semi-interpretable probabilistic models |
| 23 November 2018 | 3:30pm | large lecture theatre | Ricardo Silva [UCL] | Neural Networks and Graphical Models for Constructing and Fitting Cumulative Distribution Functions |
| 30 November 2018 | 1:30pm | TBD | Yi Yu [Bristol] | Optimal Change Point Detection and Localization in Sparse Dynamic Networks |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 23 April 2018 | 3:30pm | small lecture theatre | Aaditya Ramdas [UC Berkeley] | Uniform, nonparametric, nonasymptotic confidence sequences (or: how to test if a coin is biased) |
| 27 April 2018 | 3:30pm | small lecture theatre | Benedict Leimkuhler [University of Edinburgh] | Efficient algorithms for high-dimensional sampling based on extended stochastic dynamics |
| 23 May 2018 | 11am | small lecture theatre | Volkan Cevher [EPFL] | Mirrored Langevin Dynamics |
| 25 May 2018 | 3:30pm | small lecture theatre | Nick Whiteley [Bristol] | The Viterbi process and parallelized estimation in high-dimensions |
| 1 June 2018 | 2:00pm | small lecture theatre | Quentin Berthet [Cambridge] | Optimal Link Prediction with Matrix Logistic Regression |
| 1 June 2018 | 3:30pm | small lecture theatre | Stefano Favaro [Torino] | A Bayesian approach to disclosure risk assessment |
| 15 June 2018 | 3:30pm | small lecture theatre | Ryota Tomioka [MSR] | Gaussian Embedding of Knowledge Bases and Application to Question Answering |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 26 January 2018 | 3:30pm | small lecture theatre | Jovana Mitrovic [Oxford Statistics] | Causal Inference via Kernel Deviance Measures |
| Kaspar Märtens [Oxford Statistics] | Augmented Ensemble MCMC with applications to Factorial Hidden Markov Models | |||
| 2 February 2018 | 3:30pm | small lecture theatre | Giuseppe Di Benedetto [Oxford Statistics] | Non-exchangeable random partition models for micro clustering |
| Maxime Rischard [Harvard] | Addressing time of measurement bias in records of daily temperature extrema: a spatio-temporal imputation strategy | |||
| 9 February 2018 | 3:30pm | small lecture theatre | Michael Golden [Oxford Statistics] | Probabilistic Inference of Nucleotide Coevolution |
| 16 February 2018 | 3:30pm | small lecture theatre | Matt Kusner [Warwick and ATI] | Grammar Variational Autoencoder |
| 2 March 2018 | 2pm | small lecture theatre | Owen Thomas [University of Oslo] | Recent Methods in Model-Based Likelihood-Free Inference |
| 2 March 2018 | 3:30pm | small lecture theatre | Ingo Steinwart [University of Stuttgart] | Learning with (Flexible) Kernels |
| 7 March 2018 | 3:30pm | small lecture theatre | John Cunningham [Columbia University] | Structure in tensor-variate data: a trivial byproduct of simpler phenomena? |
| 9 March 2018 | No CSML seminar. Department Distinguished Seminar. | |||
| 12 March 2018 | 3:30pm | small lecture theatre | Sam Livingstone [UCL] | What we talk about when we talk about non-reversible MCMC |
| 16 March 2018 | No CSML seminar---room available due to industry event | |||
| 23 March 2018 | 3:30pm | small lecture theatre | Miklos Racz [Princeton University] | High-dimensional random geometric graphs |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 13 October 2017 | 3:30pm | small lecture theatre | Catalina Vallejos [UCL and ATI] | BASiCS: dealing with technical and biological noise in single-cell expression data |
| 20 October 2017 | 3:30pm | small lecture theatre | Yarin Gal [Oxford CS] | Bayesian deep learning |
| 27 October 2017 | 3:30pm | small lecture theatre | Pawan Kumar [Oxford Engineering Science] | Relaxations and Rounding for the Labelling Problem |
| 3 November 2017 | 3:30pm | small lecture theatre | Sergio Bacallado [Cambridge] | Unbiased estimation and prediction in the hierarchical two-parameter Poisson-Dirichlet process |
| 10 November 2017 | 3:30pm | small lecture theatre | Peter Orbanz [Columbia Univ., NYC] | Inference from a single, growing graph |
| 17 November 2017 | 3:30pm | small lecture theatre | Silvia Chiappa [DeepMind] | Explicit-Duration Markov Switching Models |
| 24 November 2017 | No CSML seminar. Department Distinguished Seminar. | |||
| 1 December 2017 | 3:30pm | small lecture theatre | Sara Wade [Warwick] | Adaptive truncation of a Bayesian nonparametric multivariate regression model for a study of fertility and partnership patterns of Colombian women |
| 8 December 2017 | 3:30pm | small lecture theatre | Rajen Shah [Cambridge] | The xyz algorithm for fast interaction search in high-dimensional data |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 22 March 2017 | 3:30pm | small lecture theatre | Kenji Fukumizu [Institute of Statistical Mathematics, Tokyo] | Kernel methods for topological data analysis |
| 17 March 2017 | 3:30pm | small lecture theatre | Thomas E. Nichols [University of Warwick] | Large Scale Evaluation of Random Field Theory Inference in fMRI |
| 16 March 2017 | 10:00am | small lecture theatre | Nicholas Chopin [ENSAE] | Leave Pima Indians alone: binary regression as a benchmark for Bayesian computation |
| 24 February 2017 | 3:30pm | small lecture theatre | Abdul-Lateef Haji-Ali [Oxford Maths] | Multilevel and Multi-index Monte Carlo methods for the McKean-Vlasov equation |
| 17 February 2017 | 3:30pm | small lecture theatre | Nikolas Kantas [Imperial College London] | Towards particle filtering for signals arising from dissipative stochastic PDEs |
| 10 February 2017 | 3:30pm | small lecture theatre | Gersende Fort [IMT-CNRS, Toulouse, France] | Convergence |
| of perturbed proximal gradient algorithms | ||||
| 3 February 2017 | 3:30pm | small lecture theatre | Dougal Sutherland [Gatsby] | Generative Models and Model Criticism via Optimized Maximum Mean Discrepancy |
| Date | Time | Location | Speaker | Topic |
|---|---|---|---|---|
| 25 November 2016 | 3:30pm | small lecture theatre | Chang-Han Rhee [CWI Amsterdam] | TBA |
| 18 November 2016 | 3:30pm | small lecture theatre | Jean-Michel Marin [Université de Montpellier] | Approximate Bayesian Computation using Random Forests |
| 14 November 2016 | 2:30pm | small lecture theatre | Mladen Kolar [University of Chicago] | Inference in high-dimensional semi-parametric graphical models |
| 11 November 2016 | 3:30pm | small lecture theatre | Colin Fox [University of Otaga] | MH-MCMC with Stochastic AR(1) Proposals |
| 4 November 2016 | 3:30pm | small lecture theatre | Satish Iyengar [University of Pittsburgh] | Applications of Diffusion Models to Neuroscience and Finance |
| 28 October 2016 | 3:30pm | small lecture theatre | Alexandre Bouchard-Côté [University of British Columbia] | Monte Carlo without rejection |
| 21 October 2016 | 1:30pm-3:30pm | small lecture theatre | Hong Ge [Cambridge], Simon Byrne [UCL] | Turing: A fast imperative probabilistic programming language and Introduction to Julia |
Earlier seminars are listed on our old website.