| 2025 | AISTATS | Training Neural Samplers with Reverse Diffusive KL Divergence. | Jiajun He, Wenlin Chen, Mingtian Zhang, David Barber, Jos Miguel Hernndez-Lobato |
| 2025 | COMPSAC | Automatic Diagnosis of Hip and Knee Osteoarthritis from Medical Text Records. | Jiahao Cai, Vidhi Kokel, Farhana H. Zulkernine, John A. Queenan, David Barber |
| 2025 | EMNLP | From Characters to Tokens: Dynamic Grouping with Hierarchical BPE. | Rares Dolga, Lucas Maystre, Tudor Berariu, David Barber |
| 2025 | ICLR | Improving Probabilistic Diffusion Models With Optimal Diagonal Covariance Matching. | Zijing Ou, Mingtian Zhang, Andi Zhang, Tim Z. Xiao, Yingzhen Li, David Barber |
| 2024 | ICML | Diffusive Gibbs Sampling. | Wenlin Chen, Mingtian Zhang, Brooks Paige, Jos Miguel Hernndez-Lobato, David Barber |
| 2024 | ICML | Active Preference Learning for Large Language Models. | William Muldrew, Peter Hayes, Mingtian Zhang, David Barber |
| 2022 | MICCAI | Prognostic Imaging Biomarker Discovery in Survival Analysis for Idiopathic Pulmonary Fibrosis. | An Zhao, Ahmed H. Shahin, Yukun Zhou, Eyjolfur Gudmundsson, Adam Szmul, Nesrin Mogulkoc, Frouke Van Beek, Christopher Brereton, Hendrik W. Van Es, Katarina Pontoppidan, Recep Savas, Timothy Wallis, Omer Unat, Marcel Veltkamp, Mark G. Jones, Coline H. M. Van Moorsel, David Barber, Joseph Jacob, Daniel C. Alexander |
| 2021 | ACML | Improving Gaussian mixture latent variable model convergence with Optimal Transport. | Benoit Gaujac, Ilya Feige, David Barber |
| 2021 | ICLR | Reducing the Computational Cost of Deep Generative Models with Binary Neural Networks. | Thomas Bird, Friso H. Kingma, David Barber |
| 2021 | ICML | Addressing Catastrophic Forgetting in Few-Shot Problems. | Pau Ching Yap, Hippolyt Ritter, David Barber |
| 2020 | ICLR | HiLLoC: lossless image compression with hierarchical latent variable models. | James Townsend, Thomas Bird, Julius Kunze, David Barber |
| 2020 | ICML | Spread Divergence. | Mingtian Zhang, Peter Hayes, Thomas Bird, Raza Habib, David Barber |
| 2019 | CVPR | Tracking by Animation: Unsupervised Learning of Multi-Object Attentive Trackers. | Zhen He, Jian Li, Daxue Liu, Hangen He, David Barber |
| 2019 | ICLR | Auxiliary Variational MCMC. | Raza Habib, David Barber |
| 2019 | ICLR | Practical lossless compression with latent variables using bits back coding. | James Townsend, Thomas Bird, David Barber |
| 2018 | AAAI | Generating Sentences Using a Dynamic Canvas. | Harshil Shah, Bowen Zheng, David Barber |
| 2018 | ICLR | A Scalable Laplace Approximation for Neural Networks. | Hippolyt Ritter, Aleksandar Botev, David Barber |
| 2017 | AISTATS | Complementary Sum Sampling for Likelihood Approximation in Large Scale Classification. | Aleksandar Botev, Bowen Zheng, David Barber |
| 2017 | ICML | Practical Gauss-Newton Optimisation for Deep Learning. | Aleksandar Botev, Hippolyt Ritter, David Barber |
| 2017 | IJCNN | Nesterov's accelerated gradient and momentum as approximations to regularised update descent. | Aleksandar Botev, Guy Lever, David Barber |
| 2017 | IJCNN | Overdispersed variational autoencoders. | Harshil Shah, David Barber, Aleksandar Botev |
| 2014 | ICML | Gaussian Processes for Bayesian Estimation in Ordinary Differential Equations. | David Barber, Yali Wang |
| 2013 | ESANN | Optimization by Variational Bounding. | Joe Staines, David Barber |
| 2012 | ICML | Bayesian Conditional Cointegration. | Chris Bracegirdle, David Barber |
| 2011 | UAI | Efficient Inference in Markov Control Problems. | Thomas Furmston, David Barber |
| 2008 | UAI | Clique Matrices for Statistical Graph Decomposition and Parameterising Restricted Positive Definite Matrices. | David Barber |
| 2007 | ICASSP | Stable Belief Propagation in Gaussian Dags. | David Barber, Peter Sollich |
| 2007 | ICASSP | A Bayesian Alternative to Gain Adaptation in Autoregressive Hidden Markov Models. | Bertrand Mesot, David Barber |
| 2006 | ICASSP | Efficient Kalman Smoothing for Harmonic State-Space Models. | David Barber |
| 2005 | ESANN | generative independent component analysis for EEG classification. | Silvia Chiappa, David Barber |
| 2005 | ICML | A graphical model for chord progressions embedded in a psychoacoustic space. | Jean-Franois Paiement, Douglas Eck, Samy Bengio, David Barber |
| 2004 | ICONIP | Variational Information Maximization for Neural Coding. | Felix V. Agakov, David Barber |
| 2004 | ICONIP | An Auxiliary Variational Method. | Felix V. Agakov, David Barber |
| 2003 | ICANN | Approximate Learning in Temporal Hidden Hopfield Models. | Felix V. Agakov, David Barber |
| 2003 | ICANN | Optimal Hebbian Learning: A Probabilistic Point of View. | Jean-Pascal Pfister, David Barber, Wulfram Gerstner |
| 1995 | ESANN | Knowledge and generalisation in simple learning systems. | David Barber, David Saad |