8 citations · 14 across the 10 of their papers we have counts for
11 papers
Predictively-Oriented Kalman Filtering
Zheyang Shen, Gerardo Duran-Martin, Chris. J. Oates
This paper presents a post-Bayesian approach to online filtering in nonlinear state-space models, capable of avoiding over-confident inferences in settings where either the dynamic…
Doubly Outlier-Robust Online Infinite Hidden Markov Model
Horace Yiu, Leandro Sánchez-Betancourt, Álvaro Cartea +1
We derive a robust update rule for the online infinite hidden Markov model (iHMM) for when the streaming data contains outliers and the model is misspecified. Leveraging recent adv…
A Predictive View on Streaming Hidden Markov Models
Gerardo Duran-Martin
We develop a predictive-first optimisation framework for streaming hidden Markov models. Unlike classical approaches that prioritise full posterior recovery under a fully specified…
Martingale Posterior Neural Networks for Fast Sequential Decision Making
Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Álvaro Cartea +1
We introduce scalable algorithms for online learning of neural network parameters and Bayesian sequential decision making. Unlike classical Bayesian neural networks, which induce p…
Adaptive, Robust and Scalable Bayesian Filtering for Online Learning
Gerardo Duran-Martin
In this thesis, we introduce Bayesian filtering as a principled framework for tackling diverse sequential machine learning problems, including online (continual) learning, prequent…
A unifying framework for generalised Bayesian online learning in non-stationary environments
Gerardo Duran-Martin, Leandro Sánchez-Betancourt, Alexander Y. Shestopaloff +1
We propose a unifying framework for methods that perform probabilistic online learning in non-stationary environments. We call the framework BONE, which stands for generalised (B)a…
Outlier-robust Kalman Filtering through Generalised Bayes
Gerardo Duran-Martin, Matias Altamirano, Alexander Y. Shestopaloff +5
We derive a novel, provably robust, and closed-form Bayesian update rule for online filtering in state-space models in the presence of outliers and misspecified measurement models.…
BlackJAX: Composable Bayesian inference in JAX
Alberto Cabezas, Adrien Corenflos, Junpeng Lao +19
BlackJAX is a library implementing sampling and variational inference algorithms commonly used in Bayesian computation. It is designed for ease of use, speed, and modularity by tak…
Detecting Toxic Flow
Álvaro Cartea, Gerardo Duran-Martin, Leandro Sánchez-Betancourt
This paper develops a framework to predict toxic trades that a broker receives from her clients. Toxic trades are predicted with a novel online learning Bayesian method which we ca…
Low-rank extended Kalman filtering for online learning of neural networks from streaming data
Peter G. Chang, Gerardo Durán-Martín, Alexander Y Shestopaloff +2
We propose an efficient online approximate Bayesian inference algorithm for estimating the parameters of a nonlinear function from a potentially non-stationary data stream. The met…
Efficient Online Bayesian Inference for Neural Bandits
Gerardo Duran-Martin, Aleyna Kara, Kevin Murphy
In this paper we present a new algorithm for online (sequential) inference in Bayesian neural networks, and show its suitability for tackling contextual bandit problems. The key id…