STATSCALE SEMINARS
UPCOMING SEMINARS 2022
Seminars will restart in the autumn
PREVIOUS SEMINARS
10th June 2022 - Renate Meyer (University of Auckland)
Title: Bayesian Spectral Analysis with Applications to Gravitational Wave Astronomy
27th May 2022 - Ichiro Takeuchi (Nagoya University)
13th May 2022 - Philipp Klein (Otto von Guericke University Magdeburg)
Title: Anomaly detection based on MOSUM statistics in large image data
22nd April 2022- Daren Wang (Notre Dame)
Optimal High-dimensional Change Point Testing in Regression Settings
18th March 2022 - Lan Luo (University of Iowa)
Real-Time Regression Analysis with Streaming Health Datasets
4th March 2022 - Bouchra Nasri (University of Montreal)
Change-Point Problems For Multivariate Time Series Using Pseudo-Observations
25th February 2022 - Yajun Mei (Georgia Tech)
Bandit multi-stream sequential change-point detection
4th February 2022 - Karl Hallgren (Imperial College London)
Bayesian changepoint models motivated by cyber security applications
21st January 2022 - Jacob Bien (University of Southern California)
Mixture of Multivariate Regressions Modeling for Oceanographic Flow Cytometry Data
3 December 2021 - Housen Li (University of Göttingen)
Distributional limits of graph cuts on discretized samples
19 November 2021 - Guo Yu (University of California, Santa Barbara)
Reluctant interaction modeling in generalized linear models
5 November 2021- Francesco Sanna Passino (Imperial College London)
Mutually exciting point process graphs for modelling dynamic networks
22 October 2021- Ichiro Takeuchi (Nagoya Institute of Technology)
2 July 2021 - Kevin Lin (University of Pennsylvania)
18 June 2021 - Runmin Wang (Southern Methodist University)
Dating the Break in High Dimensional Data
4 June 2021 - Abolfazl Safikhani (University of Florida)
Multiple Change Point Detection in Reduced Rank High Dimensional Vector Autoregressive Models
21th May 2021 - Hao Ni (University College London)
Sig-Wasserstein Generative models to generate realistic synthetic time series
7th May 2021 - Lynna Chu (Iowa State University)
Sequential Change-point Detection for High-Dimensional and non-Euclidean Data
26th March 2021 - Hao Chen (UC Davis)
A universal event detection framework for neuropixels data
12th March 2021 - Sumanta Basu (Cornell University)
Learning Financial Networks with Graphical Models of Time Series Data
26th February 2021 - Eric Kolaczyk (Boston University)
How hard is it to work with a network `average'?
12th February 2021 - Matteo Barigozzi (Università di Bologna)
Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm
29th January 2021 - Holger Dette (Ruhr-Universitaet Bochum)
Testing Relevant Hypotheses in Functional Time Series via Self-Normalization
4th December 2020 - Priyanga Dilini Talagala (University of Moratuwa)
Anomaly Detection in Streaming Time Series Data
20th November 2020 - Florian Pein (University of Cambridge)
About the loss function for cross-validation in change-point regression
6th November 2020 - Alex Aue (UC Davis)
Random matrix theory aids statistical inference in high dimensions
23rd October 2020 - Yoav Zemel (University of Cambridge)
Probabilistic approximations to optimal transport
9th October 2020 - Solt Kovacs (ETH Zurich)
17th July 2020 - Tobias Kley (University of Bristol)
A new approach for open-end sequential change point monitoring
3rd July, 2020 - Claudia Kirch (Otto-von-Guericke University)
Functional change point detection for fMRI data
19th June, 2020 - Martin Tveten (Dept. of Mathematics, University of Oslo)
Scalable changepoint and anomaly detection in cross-correlated data
5th June, 2020 - Yudong Chen (University of Cambridge)
High-dimensional, multiscale online changepoint detection