Warwick Machine Learning Reading Group
Our reading group takes place biweekly during term time between 3 and 4pm on Thursdays, and is currently hosted on Microsoft Teams. This usually consists of short talks on a broad range of Machine Learning topics.
To sign up to the mailing list please visit the webpage.
Organizers
(2021-2022) Harita Dellaporta & Maud Lemercier
(2020-2021) Maud Lemercier
(2019-2020) Omer Deniz Akyildiz
Past reading groups
31 March 2022, Thursday, at 3PM, by Connor Duffin
The paper/topic: Statistical finite element methods for nonlinear PDEs
17 March 2022, Thursday, at 3PM, by Jan Povala
The paper/topic: Variational Bayesian Approximation of Inverse Problems using Sparse Precision Matrices
3 March 2022, Thursday, at 3PM, by Oscar Key
The paper/topic: Composite Goodness-of-fit Tests with Kernels
17 February 2022, Thursday, at 3PM, by Fabio Zennaro
The paper/topic: Abstracting Causal Structural Models
2 December 2021, Thursday, at 3PM, by Harrison Zhu
The paper/topic: Multi-resolution Spatial Regression for Aggregated Data with an Application to Crop Yield Prediction
25 November 2021, Thursday, at 3PM, by Takuo Matsubara
The paper/topic: Robust Generalised Bayesian Inference for Intractable Likelihoods
11 November 2021, Thursday, at 3PM, by Ollie Hamelijnck
The paper/topic: Spatio-Temporal Variational Gaussian Processes
21 October 2021, Thursday, at 3PM, by Patrick O’Hara
The paper/topic: Software toolkit for machine learning projects
17 June 2021, Thursday, at 3PM, by Alan Chau
The paper/topic: BayeSIMP: Uncertainty Quantification for Causal Data Fusion
3 June 2021, Thursday, at 3PM, by Lorenzo Pacchiardi
The paper/topic: Generalized Bayesian Likelihood-Free Inference Using Scoring Rules Estimators
18 March 2021, Thursday, at 3PM, by Nicola Branchini
The paper/topic: Causal discovery with continuous optimization
4 March 2021, Thursday, at 3PM, by Patrick O’Hara
The paper/topic: Kernels on Graphs
18 February 2021, Thursday, at 3PM, by Cris Salvi
The paper/topic: Computing the untruncated signature kernel as the solution of a Goursat problem
21 January 2021, Thursday, at 3PM, by Patrick Kidger
The paper/topic: Neural Controlled Differential Equations: continuous RNNs, irregular time series, GANs
3 December 2020, Thursday, at 3PM, by Jeremias Knoblauch
The paper/topic: Optimal Continual Learning has Perfect Memory and is NP-hard
5 November 2020, Thursday, at 3PM, by Ayman Boustati
The paper/topic: Generalized Bayesian Filtering via Sequential Monte Carlo
22 October 2020, Thursday, at 3PM, by Nicola Branchini
The paper/topic: Optimized Auxiliary Particle Filters
1 October 2020, Thursday, at 3PM, by Nicola Branchini
The paper/topic: Gaussian Processes for Aggregated Data
17 September 2020, Thursday, at 3PM, by Maud Lemercier
The paper/topic: Sparse Gaussian Processes with Spherical Harmonic Features (Paper reading)
3 September 2020, Thursday, at 3PM, by Virgina Aglietti
The paper/topic: Multi-task Causal Learning with Gaussian Processes
20 August 2020, Thursday, at 3PM, by Juan Maroñas
The paper/topic: Transforming Gaussian Processes With Normalizing Flows
27 February 2020, Thursday, at 3PM, George Wynne, @Lovelace room, 1st floor.
The paper/topic: Convergence Guarantees for Gaussian Process Approximations Under Several Observation Models
20 February 2020, Thursday, at 3PM, Neil Dhir, @Turingery room, 4th floor.
The paper/topic: Gaussian Processes, Lions, Robots, Parkinson’s disease, Causal Inference, Cramer–Rao Bound and Empowerment - how I stopped worrying and learned to love Bayesian nonparametrics.
13 February 2020, Thursday, at 3PM, None
Cancelled by the speaker.
6 February 2020, Thursday, at 3PM, None
Cancelled due to the ICML deadline.
30 January 2020, Thursday, at 3PM, Virginia Aglietti
The paper/topic: Causal Bayesian Optimisation
23 January 2020, Thursday, at 3PM, James Walsh.
The paper/topic: The Conjugate Gradient Method.
Cancelled.
16 January 2020, Thursday, at 3PM, Omer Deniz Akyildiz.
(Merged with Convex Optimization group this week, Reading material: Chapter 3, Convex Optimization, S. Boyd).
12 December 2019, Thursday, at 3PM, by Ayman Boustati.
The paper/topic: Nonlinear Multitask Learning with Deep GPs
5 December 2019, Thursday, at 3PM, by Ayman Boustati.
The paper/topic: Amortized Variance Reduction for Doubly Stochastic Objectives
21 November 2019, Thursday, at 3PM, by Kathryn Leeming.
The paper/topic: Forecasting traffic speeds in Bristol using time series methods
14 November 2019, Thursday, at 3PM, by Michael Smith.
The paper/topic: Gaussian Processes for Low cost Air Pollution monitoring in Kampala
7 November 2019, Thursday, at 3PM, Daniel J. Tait.
The paper/topic: Constrained Variational Inference
24 October 2019, Thursday, at 3PM, by Theo Damoulas.
The paper: Bayesian analysis of binary and polychotomous response data [pdf]
17 October 2019, Thursday, at 3PM, by Patrick O’Hara.
1st Convex Optimization Reading Group, the book: Convex Optimization, Stephen Boyd.
3 October 2019, Thursday, at 3PM, by Ollie Hamelijnck.
The paper: Variational Fourier Features for Gaussian Processes
25 September 2019, Wednesday, at 3PM, by Omer Deniz Akyildiz.
The paper: Convergence rates for optimised adaptive importance samplers
29 July 2019, Monday, at 4PM, by Daniel J. Tait.
The paper: The Statistical Finite Element Method (Paper reading)
22 July 2019, Monday, at 4PM, by Daniel J. Tait.
The paper: The Statistical Finite Element Method (Cont.)
Background: Introduction to PDEs (2)
15 July 2019, Monday, at 4PM, by Daniel J. Tait.
The paper: The Statistical Finite Element Method
Background: Introduction to PDEs
8 July 2019, Monday, at 4PM, by Omer Deniz Akyildiz.
1 April 2019, at 3PM, by Ollie Hamelijnck.
Papers
1) State-Space Inference and Learning with Gaussian Processes
2) Identification of Gaussian Process State Space Models
1-30 March 2019, by Omer Deniz Akyildiz.
The book: Bayesian Filtering and Smoothing, Chapters 2-5 and 8