| 28 | / | 09 | / | 21 | | 3 papers accepted to NeurIPS2021: Memory Efficient Meta-Learning with Large Images, How Tight Can PAC-Bayes be in the Small Data Regime?, and Collapsed Variational Bounds for Bayesian Neural Networks |
| 25 | / | 09 | / | 21 | | A new journal paper accepted for publication: Convolutional conditional neural processes for local climate downscaling |
| 01 | / | 10 | / | 20 | | Richard Turner Promoted to Full Professor |
| 26 | / | 09 | / | 20 | | 5 papers accepted to NeurIPS2020: Continual Deep Learning by Functional Regularisation of Memorable Past (oral), Meta-Learning Stationary Stochastic Process Prediction with Convolutional Neural Processes, On the Expressiveness of Approximate Inference in Bayesian Neural Networks, Efficient Low Rank Gaussian Variational Inference for Neural Networks and VAEM: a Deep Generative Model for Heterogeneous Mixed Type Data. |
| 01 | / | 09 | / | 20 | | Siddharth Swaroop wins a 2020 Microsoft Research EMEA PhD Award |
| 01 | / | 06 | / | 20 | | 2 papers accepted to ICML2020: Scalable Exact Inference in Multi-Output Gaussian Processes, and TaskNorm: Rethinking Batch Normalization for Meta-Learning |
| 06 | / | 01 | / | 20 | | 1 paper accepted to AISTATS2020: Independent Subspace Analysis for Unsupervised Learning of Disentangled Representations |
| 20 | / | 12 | / | 19 | | 3 papers accepted to ICLR2020: Convolutional Conditional Neural Processes (oral), Continual Learning with Adaptive Weights (CLAW) and Conservative Uncertainty Estimation By Fitting Prior Networks |
| 18 | / | 10 | / | 19 | | Richard Turner awarded an EPSRC Prosperity Partnership |
| 03 | / | 09 | / | 19 | | 3 papers accepted to NeurIPS2019: Practical Deep Learning with Bayesian Principles, Icebreaker: Element-wise Active Information Acquisition with Bayesian Deep Latent Gaussian Model and Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes (spotlight oral) |
| 02 | / | 09 | / | 19 | | A new draft paper on Pathologies of Factorised Gaussian and MC Dropout Posteriors in Bayesian Neural Networks |
| 01 | / | 09 | / | 19 | | Dr. Turner becomes Director of the Machine Learning and Machine Intelligence MPhil. |
| 01 | / | 03 | / | 19 | | The new UKRI Centre for Doctoral Training in AI for the study of Environmental Risks (AI4ER) is announced. Dr. Turner is a co-Director. |
| 23 | / | 12 | / | 18 | | 2 papers accepted to AISTATS2019: The Gaussian Process Autoregressive Regression Model (GPAR) and Nonlinear ICA Using Auxiliary Variables and Generalized Contrastive Learning (oral) |
| 22 | / | 12 | / | 18 | | 2 papers accepted to ICLR2019: Meta-Learning Probabilistic Inference for Prediction and Deterministic Variational Inference for Robust Bayesian Neural Networks (oral) |
| 05 | / | 09 | / | 18 | | 2 papers accepted to NeurIPS2018: Infinite-Horizon Gaussian Processes and Geometrically Coupled Monte Carlo Sampling (spotlight oral) |
| 04 | / | 09 | / | 18 | | Tutorial on GPs presented at the Machine Learning Summer School in Madrid: Introduction to GPs, GP models, connections and applications, and Scaling GPs and handling non-linear models. |
| 02 | / | 07 | / | 18 | | Tutorial on Bayesian Deep Learning at the LVA ICA meeting |
| 11 | / | 05 | / | 18 | | 2 papers accepted to ICML2018: Structured Evolution with Compact Architectures for Scalable Policy Optimization and The Mirage of Action-Dependent Baselines in Reinforcement Learning |
| 29 | / | 01 | / | 18 | | 3 papers accepted to ICLR2018: Variational Continual Learning, Gaussian Process Behaviour in Wide Deep Neural Networks and Gradient Estimators for Implicit Models |
| 01 | / | 01 | / | 18 | | The Geometry of Random Features accepted to AISTATS2018 |
| 23 | / | 10 | / | 17 | | A Unifying Framework for Gaussian Process Pseudo-Point Approximations using Power Expectation Propagation published in JMLR |
| 05 | / | 09 | / | 17 | | Streaming Sparse Gaussian Process Approximations accepted to NIPS2017 |
| 05 | / | 09 | / | 17 | | Interpolated Policy Gradient: Merging On-Policy and Off-Policy Gradient Estimation for Deep Reinforcement Learning accepted to NIPS2017 |
| 02 | / | 06 | / | 17 | | A new draft paper: Discriminative k-shot learning using probabilistic models |
| 15 | / | 05 | / | 17 | | Two papers [1, 2] accepted to ICML2017 |
| 06 | / | 02 | / | 17 | | Q-Prop: Sample-Efficient Policy Gradient with an Off-Policy Critic accepted for oral presentation at ICLR |
| 11 | / | 17 | / | 16 | | The Multivariate Generalised von Mises: Inference and applications accepted for oral presentation at AAAI2017 |
| 23 | / | 11 | / | 16 | | Gaussian Processes: From the Basics to the State-of-the-Art, Imperial's ML tutorial series [ slides | video ] |
| 15 | / | 11 | / | 16 | | Awarded a Facebook AI Research Partnership Award (GPU server) |
| 02 | / | 11 | / | 16 | | Awarded a Google Focussed Award for Reliable and Robust Deep Reinforcement Learning with Shane Gu |
| 30 | / | 10 | / | 16 | | Dr. Cuong Nguyen and James Requeima join the group |
| 26 | / | 10 | / | 16 | | Gaussian Processes for auditory neuroscience, Imperial College London slides |
| 16 | / | 09 | / | 16 | | Machine Learning for Signal Processing keynote presentation [ slides | video ] |
| 12 | / | 08 | / | 16 | | Rényi Divergence Variational Inference accepted to NIPS2016 |
| 24 | / | 04 | / | 16 | | Deep Gaussian Processes showing state-of-the-art results on regression accepted to ICML2016 |
| 24 | / | 04 | / | 16 | | Black-box α-divergence Minimization accepted to ICML2016 |
| 04 | / | 04 | / | 16 | | Interviewed about AI by BBC 5 Live's science programme The Naked Scientist |
| 01 | / | 02 | / | 16 | | Paper accepted by AISTATS and paper accepted by Hearing Research |
| 25 | / | 11 | / | 15 | | Five papers accepted to NIPS2015 workshops, including two oral presentations and one best paper award |
| 04 | / | 09 | / | 15 | | Three papers accepted to NIPS2015, two with spotlight presentations |
| 03 | / | 07 | / | 15 | | New arxiv paper on scaling expectation propagation by Yingzhen Li, Miguel Hernandez-Lobato and Rich Turner |
| 01 | / | 07 | / | 15 | | New arxiv paper: Neural Adaptive Sequential Monte Carlo by Shane Gu, Zoubin Ghahramani and Rich Turner |
| 06 | / | 06 | / | 15 | | Thang Bui awarded a Google European Doctoral Fellowship |
| 19 | / | 05 | / | 15 | | Richard Turner awarded a Cambridge Students' Union Teaching Award for Lecturing |
| 18 | / | 03 | / | 15 | | Richard Turner awarded an EPSRC Research Grant |
| 08 | / | 12 | / | 14 | | The Group's research features on the BBC 5 Live's science programme, The Naked Scientist |
| 01 | / | 10 | / | 14 | | Shane Gu and Mateo Rojas join the group as PhD students |
| 20 | / | 09 | / | 14 | | New journal paper "Time-frequency analysis as probabilistic inference" accepted for publication |
| 09 | / | 09 | / | 14 | | Tree structured Gaussian Process Approximations paper accepted to NIPS2014 with spotlight presentation |
| 01 | / | 09 | / | 14 | | Felipe Tobar joins the group as a Research Associate |
| 01 | / | 03 | / | 14 | | Postdoctoral position available in the group |
| 28 | / | 10 | / | 13 | | The Group's research features on the BBC World Service's technology programme, Click |
| 05 | / | 10 | / | 13 | | PhD students Alex Navarro, Yingzhen Li and Thang Bui join the group |
| 02 | / | 10 | / | 13 | | news article published in Wired Magazine about the group's research |
| 07 | / | 05 | / | 13 | | Richard Turner awarded an EPSRC First Grant |
| 22 | / | 02 | / | 13 | | Richard Turner awarded a Google Faculty Award |
| 01 | / | 02 | / | 13 | | Richard Turner awarded a de Turkhiem Grant from Trinity College Cambridge |
| 01 | / | 09 | / | 12 | | Richard Turner appointed Lecturer in Computer Vision and Machine Learning |
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