Publications

Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model

MLRG Deep Curvature

DYNOTEARS: Structure Learning from Time-Series Data

Gadam: Combining Adaptivity with Iterate Averaging Gives Greater Generalisation

Neural Architecture Search using Bayesian Optimisation with Weisfeiler-Lehman Kernel

Learning Quadratic Games on Networks

Stochastic Flows and Geometric Optimization on the Orthogonal Group

Foundations of system-wide financial stress testing with heterogeneous institutions

Can Stimulating Demand Drive Costs Down? World War II as a Natural Experiment

Online Learning for Distributed and Personal Recommendations – a Fair Approach

Bayesian Optimisation Over Multiple Continuous and Categorical Inputs

Safety Guarantees for Planning Based on Iterative Gaussian Processes

Investment Sizing with Deep Learning Prediction Uncertainties for High-Frequency Eurodollar Futures Trading

Short Memories? The Impact of SEC Enforcement on Insider Leakage

Mixture Density Conditional Generative Adversarial Network Models (MD-CGAN)

Bayes Opt Adversarial Attack

Reinforcement Learning in R

Predicting Sentence-Level Polarity Labels of Financial News Using Abnormal Stock Returns

Active Inference: Demystified and Compared

Hierarchical Indian Buffet Neural Networks for Bayesian Continual Learning

UNCLEAR: A Straightforward Method for Continual Reinforcement Learning

Robust learning-based MPC for nonlinear constrained systems

Unbounded-Time Safety Verification of Guarded LTI Models with Inputs by Abstract Acceleration

Supply and demand shocks in the COVID-19 pandemic: an industry and occupation perspective

The Effect of Regulatory Constraints on Fund Performance: New Evidence from UCITS Hedge Funds

Time Series Forecasting With Deep Learning: A Survey

Fast Agent-Based Simulation Framework of Limit Order Books with Applications to Pro-Rata Markets and the Study of Latency Effects

The LL (finite) strategy for optimal LL( k) parsing

Use of Machine Learning Techniques to Create a Credit Score Model for Airtime Loans

Using Machine Learning and Remote Sensing to Value Property in Kigali

Quick or Cheap? Breaking Points in Dynamic Markets

A Vaccination Policy by Zones

Green-zone travelling: A pan-European approach to save tourism

Formal and Efficient Control Synthesis for Continuous-Time Stochastic Processes

Deep Learning for Portfolio Optimisation

Ready Policy One: World Building Through Active Learning

Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio

Deep Reinforcement Learning for Trading

Purchase Patterns, Socioeconomic Status and Political Inclination

Hedging Non-tradable Risks with Transaction Costs and Price Impact

VIGN: Variational Integrator Graph Networks

Propagative Broad Learning for Nonparametric Modeling of Ambient Effects on Structural Health Indicators

Spoofing and Price Manipulation in Order-Driven Markets

Improving VAEs’ Robustness to Adversarial Attack

Learning Bijective Feature Maps for Linear ICA

One-Shot Bayes Opt with Probabilistic Population Based Training

Effective Diversity in Population-Based Reinforcement Learning

Zero-Shot and Few-Shot Time Series Forecasting with Ordinal Regression Recurrent Neural Networks

An Overview of Gaussian Process Regression for Volatility Forecasting

Machine Learning-Based Financial Statement Analysis

HumBug Zooniverse: A Crowd-Sourced Acoustic Mosquito Dataset

Using Sparse Gaussian Processes for Predicting Robust Inertial Confinement Fusion Implosion Yields

Kernels for Sequentially Ordered Data

An Introduction to Machine Learning

Measuring Productivity Dispersion: a Parametric Approach Using the Lévy Alpha-stable Distribution

Emergent Inequality and Endogenous Dynamics in a Simple Behavioral Macroeconomic Model

A Simulation of the Insurance Industry: The Problem of Risk Model Homogeneity

Optimal Pricing in Black Box Producer-Consumer Stackelberg Games using Revealed Preference Feedback

Scenario-Free Analysis of Financial Stability with Interacting Contagion Channels

Quantum Algorithms for Training Gaussian Processes

Disentangling to Cluster: Gaussian Mixture Variational Ladder Auto-Encoders

European Option Pricing with Stochastic Volatility Models Under Parameter Uncertainty

A General Framework for Fair Regression

Indian Buffet Neural Network for Continual Learning

Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation

Enhancing Time Series Momentum Strategies Using Deep Neural Networks

Be Careful What You Ask For: Fundraising Strategies in Equity Crowdfunding

A Machine Learning Approach to Risk Minimisation in Electricity Markets

Pricing Poseidon: Extreme Weather Uncertainty and Firm Return Dynamics

A Probabilistic Approach to Nonparametric Local Volatility

Prime Broker Exposures, Collateral, and Resilience in Hedge Fund Credit Networks

The Effects of the Volcker Rule on Corporate Bond Trading: Evidence from the Underwriting Exemption

The Atalanta Effect: How High-Powered Compensation Reduces Risk-Taking

Gradient descent in Gaussian Random Fields as a Toy Model for High-Dimensional Optimisation in Deep Learning

The Deep Learning Limit: Are Negative Neural Network Eigenvalues Just Noise?

Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs

An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning

Super-resolution of Time-series Labels for Bootstrapped Event Detection

Closing the K-FAC Generalisation Gap Using Stochastic Weight Averaging

Extending Deep Learning Models for Limit Order Books to Quantile Regression

How Does Mini-Batching Affect Curvature Information for Second Order Deep Learning Optimization

Semi-Separable Hamiltonian Monte Carlo for Inference in Bayesian Neural Networks

WiSE-ALE: Wide Sample Estimator for Approximate Latent Embedding

Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents

Scalable Bounding of Predictive Uncertainty in Regression Problems with SLAC

Localised Kinky Inference

Machine Learning Techniques for Deciphering Implied Volatility Surface Data in a Hostile Environment: Scenario Based Particle Filter, Risk Factor Decomposition & Arbitrage Constraint Sampling

Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction

Bounding Quantiles of Wasserstein Distance Between True and Empirical Measure

Semi-supervised Learning with Deep Generative Models

DeepLOB: Deep Convolutional Neural Networks for Limit Order Books

Safe Policy Search Using Gaussian Process Models

Logically-Constrained Neural Fitted Q-Iteration

Ultra-Fast Activity and Intraday Market Quality

Market Making with Minimum Resting Times

Automated Formal Synthesis of Provably Safe Digital Controllers for Continuous Plants

Reinforcement Learning with Linear Logic Guidance

Earnings Forecasts in Mergers and Acquisitions

Are all Insider Sales Created Equal? First Evidence from Supplementary Disclosures on SEC Filings

Robust Data-Based Model Predictive Control for Nonlinear Constrained Systems

Online Optimisation for Online Learning and Control – From No-Regret to Generalised Error Convergence

Foreign Exchange Markets with Last Look Mathematics and Financial Economics

Learning Graphs from Data: A Signal Representation Perspective

Ultra-Fast Activity and Intraday Market Quality

StocHy: Automatic Verification and Synthesis of Stochastic Processes

Efficiency Through Uncertainty: Scalable Formal Synthesis for Stochastic Hybrid Systems

Solving Strong-Substitutes Product-Mix Auctions

The Hairy Ball Problem is PPAD-Complete

Hedge Fund Performance: Are Stylized Facts Sensitive to Which Database One Uses?

Entropic Graph Spectrum

Adversarial Robustness Guarantees for Classification with Gaussian Processes

Hyperbolic development and inversion of signature

How well do Experience Curves Predict Technological Progress? A Method for Making Distributional Forecasts

Customer Segmentation for East African Microgrid Consumers

Forecasting Energy Demand for Microgrids Over Multiple Horizons

Persistence Paths and Signature Features in Topological Data Analysis

BDLOB: Bayesian Deep Convolutional Neural Networks for Limit Order Books

Modelling Analysts’ Recommendations via Bayesian Machine Learning

Dual Attainment for the Martingale Transport Problem

Pointwise Arbitrage Pricing Theory in Discrete Time

The Robust Pricing – Hedging Duality for American Options in Discrete Time Financial Markets

Two Explicit Skorokhod Embeddings for Simple Symmetric Random Walk

The Root Solution to the Multi-Marginal Embedding Problem: An Optimal Stopping and Time-Reversal Approach

Time–Consistent Investment Under Model Uncertainty: The Robust Forward Criteria

Robust Pricing–Hedging Duality in Continuous Time

Pathwise Stochastic Calculus with Local Times

An Iterated Azéma-Yor Type Embedding for Finitely Many Marginals

Robust Pricing and Hedging Under Trading Restrictions and the Emergence of Local Martingale Models

A Bayesian Optimization Approach to Compute the Nash Equilibria of Potential Games using Bandit Feedback

Naked Aggression: Personality and Portfolio Manager Performance

Optimal Hedge Tracking Portfolios in a Limit Order Book

Economic Uncertainty, Trading Activity, and Commodity Futures Volatility

Stochastic Volatility for Utility Maximisers – A Martingale Approach

Volatility is Log-Normal – but not for the reason you think

BCCNet: Bayesian Classifier Combination Neural Network

MOrdRed: Memory-based Ordinal Regression Deep Neural Networks for Time Series Forecasting

Practical Bayesian Learning of Neural Networks via Adaptive Subgradient Methods

Bayesian Nonparametrics and Feedback-Linearisation of Discretised Conrol-Affine Systems

Sequential Sampling of Gaussian Latent Variable Models

Bioacoustic Detection with Wavelet-Conditioned Convolutional Neural Networks

Improved Stochastic Trace Estimation Using Mutually Unbiased Bases

Optimization, Fast and Slow: Optimally Switching Between Local and Bayesian Optimization

Tropical Abstractions of Max-Plus Linear Systems

Thresholded ConvNet Ensembles: Neural Networks for Technical Forecasting

Loss-Calibrated Approximate Inference in Bayesian Neural Networks

Linear Quadratic Regulation of Polytopic Time-inhomogeneous Markov Jump Linear Systems

Entropic Spectral Learning in Large Scale Networks

Nonlinear Set Membership Regression with Adaptive Hyper-Parameter Estimation for Online Learning and Control

Identifying Sources and Sinks in the Presence of Multiple Agents with Gaussian Process Vector Calculus

Provenance Network Analytics: An Approach to Data Analytics Using Data Provenance

Learning Against Non-Stationary Agents with Opponent Modelling and Deep Reinforcement Learning

Deploying Novel Exploration Techniques (NETs) for Malaria Policy Interventions

Bayesian Optimization of Personalised Models for Patient Vital-Sign Monitoring

Impact of Solar Panels and Cooling Devices on Frequency Control after a Generation Loss Incident

Proceedings of the 6th IFAC Conference on Analysis and Design of Hybrid Systems

Maintenance of Smart Buildings Using Fault Trees

Symbolic Abstractions of Networked Control Systems

Do U.S. Analysts Improve the Local Information Environment of Cross-Listed Stocks?

Distributed Optimization for Energy Management in Building Networks

Algorithmic Trading, Stochastic Control and Mutually Exciting Processes

Technical Uncertainty in Real Options with Learning Journal of Energy Markets

Lazily Adapted Constant Kinky Inference for Nonparametric Regression and Model-Reference Adaptive Control

Behavioural Attributes and Financial Churn Prediction

Methods for Quantifying Effects of Social Unrest Using Credit Card Transaction Data

Market Making with Minimum Resting Times

Social Bridges in Urban Purchase Behaviour ACM Transactions on Intelligent Systems and Technology

Modelling Smart Buildings Using Fault Maintenance Trees

Experimental Biological Protocols with Formal Semantics

Multi-unit Bilateral Trade

Prediction of Tidal Currents Using Bayesian Machine Learning

Super-multiplicativity and a lower bound for the decay of the signature of a path of finite length

Gaussian Process Regression for In-situ Capacity Estimation of Lithium-ion Batteries

Adaptive Geometric Learning for Optimization and Sampling

Rotation-free Online Handwritten Character Recognition using Dyadic Path Signature Features, Hanging Normalization, and Deep Neural Network

Fast Information-theoretic Bayesian Optimisation

Detecting early signs of depressive and manic episodes in patients with bipolar disorder using the signature-based model

Battery Capacity Estimation from Partial-Charging Data Using Gaussian Process Regression

Empirical Prediction Intervals Improve Energy Forecasting

Distributionally Robust Optimization Techniques in Batch Bayesian Optimization

The Numeraire Property and Long-Term Growth Optimality for Drawdown-Constrained Investments

Investor Concentration, Flows, and Cash Holdings: Evidence from Hedge Fund

Risk-Minimisation in Electricity Markets: Fixed Price, Unknown Consumption

Hedging Local Volume Risk Using Forward Markets: Nordic Case Energy Economics

The Fundamental Theorem of Derivatives Trading – Exposition, Extensions and Experiments

Introducing the HFTE Model: A Multi-Species Predator-Prey Ecosystem for High Frequency Quantitative Financial Strategies

High-Dimensional Time Series Prediction Using Kernel-Based Koopman Mode Regression

Risk Management with Weighted VaR

Inferring Agent Objectives at Different Scales of a Complex Adaptive System

MiDGaP: Mixture Density Gaussian Processes

Reading Tea Leaves: A Neural Network Perspective on Technical Trading

Portfolio Optimization in the Context of Cointelated Pairs: Stochastic Differential Equation vs. Machine Learning Approach

Deciphering Price Formation in the High Frequency Domain: Systems & Evolutionary Dynamics as Keys for Construction of the High Frequency Trading Ecosystem

A Proposed Risk Modeling Shift from the Approach of Stochastic Differential Equation Towards Machine Learning Clustering: Illustration with the Concepts of Anticipative & Responsible VaR

Convergence of Heston to SVI Proposed Extensions: Rational & Conjecture for the Convergence of Extended Heston to the Implied Volatility Surface Parametrization

Cost-Sensitive Detection with Variational Autoencoders for Environmental Acoustic Sensing

Improving Photometric Redshift Estimation Using GPz: size information, post processing and improved photometry.

Entropic Determinants of Massive Matrices

Robust Open-Source Removal of Systematics in Kepler Data

Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources

Optimal Client Recommendation for Market Makers in Illiquid Financial Products

A Novel Approach to Forecasting Financial Volatility with Gaussian Process Envelopes

Entropic Trace Estimates for Log Determinants

An Information and Field Theoretic Approach to the Gran Canonical Ensemble

Bayesian Inference of Log Determinants

Formal Control Synthesis via Simulation Relations and Behavioural Theory for Discrete-Time Descriptor Systems

Practical Bayesian Optimization for Variable Cost Objectives

Distribution of Gaussian Process Arc Lengths

Bayesian Optimisation of Gaussian Processes for Identifying the Deteriorating Patient

Identifying Sources of Discrimination Risk in the Life Cycle of Machine Intelligence Applications Under New European Union Regulations

Lipschitz Optimisation for Lipschitz Interpolation

Learning-Based Nonlinear Model Predictive Control

Learning Heat Diffusion Graphs

The Rippling Effect of Social Influence in Phone Communication Network

A signature-based machine learning model for bipolar disorder and borderline personality disorder

Alternating Optimisation and Quadrature for Robust Control

The signature of a rough path: Uniqueness

A Macine Learning Approach to the Prediction of Tidal Currents

Characteristic Functions of Measures on Geometric Rough Paths

Preconditioning Kernel Matrices

Discretely sampled signals and the rough Hoff process

Bayesian Optimization for Probabilistic Programs

Glasses: Relieving the Myopia of Bayesian Optimisation

Robust Trading of Implied Skew

Path-Dependent and Randomized Strategies in Barberis’ Casino Gambling Model

The Maximum Maximum of Martingales with given n Marginals

The Incentives of Hedge Fund Fees and High-Water Marks

Equity Crowdfunding: A New Phenomena

Herding in Equity Crowdfunding

Market Dominance in Bond and CDS Interdealer Networks

Extracting Predictive Information from Heterogeneous Data Streams Using Gaussian Processes

The Statistical Significance of Multivariate Hawkes Processes Fitted to Limit Order Book Data

Deviations in Expected Price Impact for Small Transaction Volumes Under Fee Restructuring

Using Real-Time Cluster Configurations of Streaming Asynchronous Features as Online State Decriptors in Financial Markets

Detecting Intraday Financial Market States Using Temporal Clustering

High-Speed Detection of Emergent Market Clustering via an Unsupervised Parallel Genetic Algorithm

A Framework for Assessing the Performance of Pulsar Search Pipelines

A Disaster Response System Based on Human-Agent Collectives

String and Membrane Gaussian Processes

GPz: Non-Stationary Sparse Gaussian Processes for Heteroscedastic Uncertainty Estimation in Photometric Redshift

Latent Point Process Allocation

No-Regret Learning and a Mechanism for Distributed Multiagent Planning

Speculative Trading of Electricity Contracts in Interconnected Locations Energy Economics

Multi-Modal Image Retrieval with Random Walk on Multi-Layer Graphs

Learning Laplacian Matrix in Smooth Graph Signal Representations

The Future of Employment: How Susceptible are Jobs to Computerisation?

System for Identifying, Monitoring and Ranking Incidents From Social Media

How Market Ecology Explains Market Malfunction