Tom Diethe

Orcid: 0000-0002-0776-5407

Affiliations:
  • AstraZeneca, Cambridge, UK
  • University of Bristol, UK (former)
  • University College London, UK (former)


According to our database1, Tom Diethe authored at least 48 papers between 2007 and 2024.

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Bibliography

2024
DeCoRe: Decoding by Contrasting Retrieval Heads to Mitigate Hallucinations.
CoRR, 2024

Improving Antibody Humanness Prediction using Patent Data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Measures of diversity and space-filling designs for categorical data.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

An Image is Worth Multiple Words: Discovering Object Level Concepts using Multi-Concept Prompt Learning.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

Tackling Structural Hallucination in Image Translation with Local Diffusion.
Proceedings of the Computer Vision - ECCV 2024, 2024

2023
An Image is Worth Multiple Words: Learning Object Level Concepts using Multi-Concept Prompt Learning.
CoRR, 2023

Unlocking the Heart Using Adaptive Locked Agnostic Networks.
CoRR, 2023

2021
Continual Density Ratio Estimation in an Online Setting.
CoRR, 2021

2020
Automatic Discovery of Privacy-Utility Pareto Fronts.
Proc. Priv. Enhancing Technol., 2020

Interpretable Anomaly Detection with Mondrian P{ó}lya Forests on Data Streams.
CoRR, 2020

Bypassing Gradients Re-Projection with Episodic Memories in Online Continual Learning.
CoRR, 2020

Similarity of Neural Networks with Gradients.
CoRR, 2020

Hyperbolic Embeddings for Preserving Privacy and Utility in Text.
Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Calibrating Mechanisms for Privacy Preserving Text Analysis.
Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Preserving Privacy in Analyses of Textual Data.
Proceedings of the PrivateNLP 2020: Workshop on Privacy in Natural Language Processing, 2020

Optimal Continual Learning has Perfect Memory and is NP-hard.
Proceedings of the 37th International Conference on Machine Learning, 2020

2019
An application of hierarchical Gaussian processes to the detection of anomalies in star light curves.
Neurocomputing, 2019

HyperStream: a Workflow Engine for Streaming Data.
CoRR, 2019

Facilitating Bayesian Continual Learning by Natural Gradients and Stein Gradients.
CoRR, 2019

Privacy-preserving Active Learning on Sensitive Data for User Intent Classification.
CoRR, 2019

Continual Learning in Practice.
CoRR, 2019

β<sup>3</sup>-IRT: A New Item Response Model and its Applications.
CoRR, 2019

Distribution calibration for regression.
Proceedings of the 36th International Conference on Machine Learning, 2019

Leveraging Hierarchical Representations for Preserving Privacy and Utility in Text.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

$β^3$-IRT: A New Item Response Model and its Applications.
Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2018
A Comprehensive Study of Activity Recognition Using Accelerometers.
Informatics, 2018

Releasing eHealth Analytics into the Wild: Lessons Learnt from the SPHERE Project.
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

Anomaly detection in star light curves using hierarchical Gaussian processes.
Proceedings of the 26th European Symposium on Artificial Neural Networks, 2018

2017
Unsupervised learning of sensor topologies for improving activity recognition in smart environments.
Neurocomputing, 2017

Probabilistic Sensor Fusion for Ambient Assisted Living.
CoRR, 2017

2016
On the need for structure modelling in sequence prediction.
Mach. Learn., 2016

The SPHERE Challenge: Activity Recognition with Multimodal Sensor Data.
CoRR, 2016

BDL.NET: Bayesian dictionary learning in Infer.NET.
Proceedings of the 26th IEEE International Workshop on Machine Learning for Signal Processing, 2016

ADL™: A Topic Model for Discovery of Activities of Daily Living in a Smart Home.
Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence, 2016

Active transfer learning for activity recognition.
Proceedings of the 24th European Symposium on Artificial Neural Networks, 2016

2015
Bridging e-Health and the Internet of Things: The SPHERE Project.
IEEE Intell. Syst., 2015

An RSSI-based wall prediction model for residential floor map construction.
Proceedings of the 2nd IEEE World Forum on Internet of Things, 2015

Bayesian Modelling of the Temporal Aspects of Smart Home Activity with Circular Statistics.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2015

2013
Online Learning with (Multiple) Kernels: A Review.
Neural Comput., 2013

2012
Data dependent kernels in nearly-linear time.
Proceedings of the Fifteenth International Conference on Artificial Intelligence and Statistics, 2012

2011
Preface.
Proceedings of the Second Workshop on Applications of Pattern Analysis, 2011

2010
Sparse machine learning methods with applications in multivariate signal processing.
PhD thesis, 2010

Preface.
Proceedings of the First Workshop on Applications of Pattern Analysis, 2010

Constructing Nonlinear Discriminants from Multiple Data Views.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2010

2009
Matching Pursuit Kernel Fisher Discriminant Analysis.
Proceedings of the Twelfth International Conference on Artificial Intelligence and Statistics, 2009

Kernel Polytope Faces Pursuit.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2009

2007
Modelling the Effects of Colony Age on the Foraging Behaviour of Harvester Ants.
Proceedings of the Advances in Artificial Life, 9th European Conference, 2007


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