- Detection of Overshooting Tops in Deep Convective Clouds using Deep Learning
- Description Logic Embeddings for Neuro-Symbolic Reasoning
- New Benchmarks for Knowledge Graph Completion
- A Formalization And Attack Tree for Gasper: Ethereum's Proposal for Proof-of-Stake Consensus
- Video Annotation with Knowledge Graphs, using Deep Learning and Background Knowledge
- Experimental Comparison of Ansatze for Quantum Natural Language Processing
- Learning Martingales
- Improving the Relational Inductive Bias of Graph Neural Networks
- Assessing the Interpretability of Large Language Models
- Developing computational tools to aid the design of CRISPR/Cas9 gene editing experiments
- Using State-of-the-art Computer Vision Models to Build Novel Applications on Recent XR Platforms
- Neural network architectures to identify risk of Parkinson’s disease
- A unique normal form for prime-dimensional qudit Clifford ZX-calculus
- Reinforcement Learning via Predictive Coding: Revisiting Perspectives from Neuroscience in the Context of Deep Learning
- Motion Planning for Underwater Gliders
- Enhancing VAE-learning on spatial priors using graph convolutional networks
- Deep Learning for Alzheimer’s Disease Genomics
- Machine Learning Approaches for Estimating the Causal Effects of Aerosols on Clouds
- Structural Transfer Learning in Semantic Parsers
- Augmenting semi-mechanistic models with deep learning to model the SARS-CoV-2 pandemic
- Beyond MCMC: A Variational Inference Workflow
- Graphical calculus for Tensor Network Contractions
- Quantum Circuit Optimisation Through Stabiliser Reduction of Pauli Exponentials
- Portable, Low-Cost, and Low-Power mmWave Radar Imaging for Concealed Weapon Detection
- Participatory Budgeting with Conflicts and Partial Information
- Essays on Participatory Budgeting
- Assessing the performance and security characteristics of QUIC in the context of computationally constrained spacecraft
- Quantum Machine Learning using the ZXW-Calculus
- Compiling Deep Learning Workloads for Distributed Computing Clusters
- Category-theoretic syntactic models of programming languages

- Mixed Integer Linear Programming for the Train Timetabling Problem
- Developing robust machine learning models for off-target prediction in CRISPR/Cas9 gene editing using ensemble learning and feature space analysis
- Dependent Types with Borrowing
- Imitate Human in Board Games: Move Prediction in Chess and Xiangqi with Structurally Variable Networks
- Task-adaptive Continual Learning
- On Representation Learning for Deterministic Uncertainty Estimation
- Conformal time-series forecasting
- SiPPI - Predicting Protein-Protein Interactions using Deep Learning
- Deep learning for tabular data in healthcare
- Analysis and Explanation of Binarized Neural Networks using Symbolic Trajectory Evaluation
- Hypergraph MBQC in the ZH-calculus
- Associative Memories and Predictive Coding
- Quantum Computing for Graph Representation Learning
- Exploring the latent space of deep generative protein models: Applications to GPCRs
- Automated Classification of Cardiac Action Potential Phenotypes for Prediction of Drug-Induced Pro-Arrhythmic Risk
- Machine Learning in Particle Physics: Graph Neural Networks for Jet Clustering at the Future Circular Collider (FCC-ee)
- Self-supervised Single-Image 3D Face Relighting
- An Empirical Investigation of Training Speed and Generalisation
- Crafting Label Noise to Increase Adversarial Vulnerability in Deep Learning Models
- Nowcasting unemployment with real time job vacancies data in the United States
- Deep Learning models for the analysis of short tandem repeats in DNA sequences
- Security for Health An Exploration of Cybersecurity, eHealth, and Sustainable Development Goal Three
- Software implementation of Ethical Black Box, a software, which can be used to collect data about a robot’s actions in real-time and in context, to recreate and analyse its past actions
- DeDUCE: A Novel Algorithm Providing Counterfactual Explanations
- Voting and Strategic Candidacies in Primary Systems
- 4-Player Chess: An Environment and Benchmarks for Multi-Agent Reinforcement Learning
- Intent and Theory of Mind: Modelling Belief under Uncertainty
- Moving Object Detection Based On Weakly Supervised Deep Learning Method
- Novel Predictive Coding Networks that Achieve Task-Agnostic Learning
- Inference Attacks on Graph Neural Networks
- Learning to play Open Face Chinese Poker through Deep Reinforcement Learning
- Inferring Dynamic Brain Networks with RNN-VAEs on MEG Data
- Persus: A Latency and Fault Tolerance Library for Microservices Architecture in Golang
- A Box Embedding Model for Temporal Knowledge Graph Completion
- Optimizing large scale omics analyses with data management techniques
- Multi-Type Continuous Disentanglement Variational AutoEncoder Projecting multiple categorical models into a single dimensional space
- Evaluating MAP Inference for Chase-Generated Hinge-Loss Markov Random Fields
- Conversational Negation in Compositional Distributional Semantics
- Variability in Drug Response: A Comparison of Population of Models and Uncertainty Quantification for Predictions of Drug-induced Effects on the Cardiac Action Potential
- On Representation Learning for Deterministic Uncertainty Estimation
- Improving weight-sharing Neural Architecture Search with a marginal likelihood estimator
- Reinforcement Learning for Rule Selection in End to End Dierentiable Proving
- Visualising Simulated Liquid Democracy and Measuring Performance Under Changing Agent Parameters
- Cheap Talk Discovery and Utilization in Multi-Agent Reinforcement Learning