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ORCIDStephen J. Roberts
Stephen Roberts 0001
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- affiliation: University of Oxford, UK
Other persons with the same name
- Stephen Roberts — disambiguation page
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2020 – today
- 2024
[j58]Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker
, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven G. Gilmour, Stephen J. Roberts, Christopher C. Holmes:
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. Nat. Mac. Intell. 6(2): 229-242 (2024)- [i107]Wee Ling Tan, Stephen J. Roberts, Stefan Zohren:
Deep Learning for Options Trading: An End-To-End Approach. CoRR abs/2407.21791 (2024) - 2023
- [j57]Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts:
On Sequential Bayesian Inference for Continual Learning. Entropy 25(6): 884 (2023) - [j56]Julien Walden Huang, Stephen J. Roberts, Jan-Peter Calliess:
On the Sample Complexity of Lipschitz Constant Estimation. Trans. Mach. Learn. Res. 2023 (2023) - [c119]Samuel Kessler, Mateusz Ostaszewski, Michal Pawel Bortkiewicz, Mateusz Zarski, Maciej Wolczyk, Jack Parker-Holder, Stephen J. Roberts, Piotr Milos:
The Effectiveness of World Models for Continual Reinforcement Learning. CoLLAs 2023: 184-204 - [c118]Scott Alexander Cameron, Arnu Pretorius, Stephen J. Roberts:
Nonparametric Boundary Geometry in Physics Informed Deep Learning. NeurIPS 2023 - [i106]Samuel Kessler, Adam D. Cobb, Tim G. J. Rudner, Stefan Zohren, Stephen J. Roberts:
On Sequential Bayesian Inference for Continual Learning. CoRR abs/2301.01828 (2023) - [i105]Wee Ling Tan, Stephen J. Roberts, Stefan Zohren:
Spatio-Temporal Momentum: Jointly Learning Time-Series and Cross-Sectional Strategies. CoRR abs/2302.10175 (2023) - [i104]Lawrence Wang, Stephen J. Roberts:
SANE: The phases of gradient descent through Sharpness Adjusted Number of Effective parameters. CoRR abs/2305.18490 (2023) - [i103]Lawrence Wang, Stephen Roberts:
The instabilities of large learning rate training: a loss landscape view. CoRR abs/2307.11948 (2023) - [i102]Xingyue Pu, Stephen J. Roberts, Xiaowen Dong, Stefan Zohren:
Network Momentum across Asset Classes. CoRR abs/2308.11294 (2023) - [i101]Xingyue Pu, Stefan Zohren, Stephen J. Roberts, Xiaowen Dong:
Learning to Learn Financial Networks for Optimising Momentum Strategies. CoRR abs/2308.12212 (2023) - [i100]Kieran Wood, Samuel Kessler, Stephen J. Roberts, Stefan Zohren:
Few-Shot Learning Patterns in Financial Time-Series for Trend-Following Strategies. CoRR abs/2310.10500 (2023) - 2022
- [j55]Diego Granziol, Binxin Ru, Xiaowen Dong, Stefan Zohren, Michael A. Osborne, Stephen J. Roberts:
Maximum Entropy Approach to Massive Graph Spectrum Learning with Applications. Algorithms 15(6): 209 (2022) - [j54]Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen Roberts, Marta Kwiatkowska:
Adversarial Robustness Guarantees for Gaussian Processes. J. Mach. Learn. Res. 23: 146:1-146:55 (2022) - [j53]Diego Granziol, Stefan Zohren, Stephen Roberts:
Learning Rates as a Function of Batch Size: A Random Matrix Theory Approach to Neural Network Training. J. Mach. Learn. Res. 23: 173:1-173:65 (2022) - [c117]Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts:
Same State, Different Task: Continual Reinforcement Learning without Interference. AAAI 2022: 7143-7151 - [c116]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. AISTATS 2022: 9776-9792 - [c115]Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts:
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. AAMAS 2022: 1771-1773 - [c114]Shuyu Lin, Ronald Clark, Niki Trigoni, Stephen J. Roberts:
Uncertainty Estimation with a VAE-Classifier Hybrid Model. ICASSP 2022: 3548-3552 - [c113]Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts:
Robust and Scalable SDE Learning: A Functional Perspective. ICLR 2022 - [c112]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Offline Model Based Reinforcement Learning. ICLR 2022 - [c111]Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan:
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. ICML 2022: 2784-2810 - [c110]Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts:
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. ACM Multimedia 2022: 7120-7124 - [c109]Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen Roberts, Tim Rocktäschel, Edward Grefenstette:
Learning General World Models in a Handful of Reward-Free Deployments. NeurIPS 2022 - [i99]Jaleh Zand, Jack Parker-Holder, Stephen J. Roberts:
On-the-fly Strategy Adaptation for ad-hoc Agent Coordination. CoRR abs/2203.08015 (2022) - [i98]Björn W. Schuller, Anton Batliner, Shahin Amiriparian, Christian Bergler, Maurice Gerczuk, Natalie Holz, Pauline Larrouy-Maestri, Sebastian P. Bayerl, Korbinian Riedhammer, Adria Mallol-Ragolta, Maria Pateraki, Harry Coppock, Ivan Kiskin, Marianne Sinka, Stephen J. Roberts:
The ACM Multimedia 2022 Computational Paralinguistics Challenge: Vocalisations, Stuttering, Activity, & Mosquitoes. CoRR abs/2205.06799 (2022) - [i97]Edoardo Cetin, Philip J. Ball, Stephen J. Roberts, Oya Çeliktutan:
Stabilizing Off-Policy Deep Reinforcement Learning from Pixels. CoRR abs/2207.00986 (2022) - [i96]Daniel Poh, Stephen J. Roberts, Stefan Zohren:
Transfer Ranking in Finance: Applications to Cross-Sectional Momentum with Data Scarcity. CoRR abs/2208.09968 (2022) - [i95]Yingchen Xu, Jack Parker-Holder, Aldo Pacchiano, Philip J. Ball, Oleh Rybkin, Stephen J. Roberts, Tim Rocktäschel, Edward Grefenstette:
Learning General World Models in a Handful of Reward-Free Deployments. CoRR abs/2210.12719 (2022) - [i94]Samuel Kessler, Piotr Milos, Jack Parker-Holder, Stephen J. Roberts:
The Surprising Effectiveness of Latent World Models for Continual Reinforcement Learning. CoRR abs/2211.15944 (2022) - [i93]Jobie Budd, Kieran Baker, Emma Karoune, Harry Coppock, Selina Patel, Ana Tendero Cañadas, Alexander Titcomb, Richard Payne, David Hurley, Sabrina Egglestone, Lorraine Butler, Jonathon Mellor, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Radka Jersakova, Rachel A. McKendry, Peter Diggle, Sylvia Richardson, Björn W. Schuller, Steven Gilmour, Davide Pigoli, Stephen J. Roberts, Josef Packham, Tracey Thornley, Chris C. Holmes:
A large-scale and PCR-referenced vocal audio dataset for COVID-19. CoRR abs/2212.07738 (2022) - [i92]Harry Coppock, George Nicholson, Ivan Kiskin, Vasiliki Koutra, Kieran Baker, Jobie Budd, Richard Payne, Emma Karoune, David Hurley, Alexander Titcomb, Sabrina Egglestone, Ana Tendero Cañadas, Lorraine Butler, Radka Jersakova, Jonathon Mellor, Selina Patel, Tracey Thornley, Peter Diggle, Sylvia Richardson, Josef Packham, Björn W. Schuller, Davide Pigoli, Steven Gilmour, Stephen J. Roberts, Chris C. Holmes:
Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers. CoRR abs/2212.08570 (2022) - [i91]Davide Pigoli, Kieran Baker, Jobie Budd, Lorraine Butler, Harry Coppock, Sabrina Egglestone, Steven G. Gilmour, Chris C. Holmes, David Hurley, Radka Jersakova, Ivan Kiskin, Vasiliki Koutra, Jonathon Mellor, George Nicholson, Joe Packham, Selina Patel, Richard Payne, Stephen J. Roberts, Björn W. Schuller, Ana Tendero Cañadas, Tracey Thornley, Alexander Titcomb:
Statistical Design and Analysis for Robust Machine Learning: A Case Study from COVID-19. CoRR abs/2212.08571 (2022) - 2021
- [j52]Anup Aprem, Stephen Roberts:
A Bayesian Optimization Approach to Compute Nash Equilibrium of Potential Games Using Bandit Feedback. Comput. J. 64(12): 1801-1813 (2021) - [j51]Anup Aprem, Stephen J. Roberts:
Optimal pricing in black box producer-consumer Stackelberg games using revealed preference feedback. Neurocomputing 437: 31-41 (2021) - [c108]Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth:
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. AISTATS 2021: 3565-3573 - [c107]Alexander Camuto, Matthew Willetts, Chris C. Holmes, Brooks Paige, Stephen J. Roberts:
Learning Bijective Feature Maps for Linear ICA. AISTATS 2021: 3655-3663 - [c106]Matthew Willetts, Alexander Camuto, Tom Rainforth, Stephen J. Roberts, Christopher C. Holmes:
Improving VAEs' Robustness to Adversarial Attack. ICLR 2021 - [c105]Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts:
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. ICML 2021: 619-629 - [c104]Ivan Kiskin, Marianne Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Rinita Dam, Theodoros Marinos, Yunpeng Li, Dickson Msaky, Emmanuel Kaindoa, Gerard Killeen, Eva Herreros-Moya, Kathy Willis, Stephen J. Roberts:
HumBugDB: A Large-scale Acoustic Mosquito Dataset. NeurIPS Datasets and Benchmarks 2021 - [c103]Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. NeurIPS 2021: 15513-15528 - [c102]Ivan Kiskin, Adam D. Cobb, Marianne Sinka, Kathy Willis, Stephen J. Roberts:
Automatic Acoustic Mosquito Tagging with Bayesian Neural Networks. ECML/PKDD (4) 2021: 351-366 - [c101]Samuel Kessler, Vu Nguyen, Stefan Zohren, Stephen J. Roberts:
Hierarchical Indian buffet neural networks for Bayesian continual learning. UAI 2021: 749-759 - [c100]Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts:
Towards tractable optimism in model-based reinforcement learning. UAI 2021: 1413-1423 - [i90]Arno Blaas, Stephen J. Roberts:
The Effect of Prior Lipschitz Continuity on the Adversarial Robustness of Bayesian Neural Networks. CoRR abs/2101.02689 (2021) - [i89]Philip J. Ball, Stephen J. Roberts:
OffCon3: What is state of the art anyway? CoRR abs/2101.11331 (2021) - [i88]Andrea Patane, Arno Blaas, Luca Laurenti, Luca Cardelli, Stephen J. Roberts, Marta Kwiatkowska:
Adversarial Robustness Guarantees for Gaussian Processes. CoRR abs/2104.03180 (2021) - [i87]Philip J. Ball, Cong Lu, Jack Parker-Holder, Stephen J. Roberts:
Augmented World Models Facilitate Zero-Shot Dynamics Generalization From a Single Offline Environment. CoRR abs/2104.05632 (2021) - [i86]Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Enhancing Cross-Sectional Currency Strategies by Ranking Refinement with Transformer-based Architectures. CoRR abs/2105.10019 (2021) - [i85]Kieran Wood, Stephen J. Roberts, Stefan Zohren:
Slow Momentum with Fast Reversion: A Trading Strategy Using Deep Learning and Changepoint Detection. CoRR abs/2105.13727 (2021) - [i84]Lewis Smith, Joost van Amersfoort, Haiwen Huang, Stephen J. Roberts, Yarin Gal:
Can convolutional ResNets approximately preserve input distances? A frequency analysis perspective. CoRR abs/2106.02469 (2021) - [i83]Samuel Kessler, Jack Parker-Holder, Philip J. Ball, Stefan Zohren, Stephen J. Roberts:
Same State, Different Task: Continual Reinforcement Learning without Interference. CoRR abs/2106.02940 (2021) - [i82]Saad Hamid, Sebastian Schulze, Michael A. Osborne, Stephen J. Roberts:
Marginalising over Stationary Kernels with Bayesian Quadrature. CoRR abs/2106.07452 (2021) - [i81]Jack Parker-Holder, Vu Nguyen, Shaan Desai, Stephen J. Roberts:
Tuning Mixed Input Hyperparameters on the Fly for Efficient Population Based AutoRL. CoRR abs/2106.15883 (2021) - [i80]Shaan Desai, Marios Mattheakis, David Sondak, Pavlos Protopapas, Stephen J. Roberts:
Port-Hamiltonian Neural Networks for Learning Explicit Time-Dependent Dynamical Systems. CoRR abs/2107.08024 (2021) - [i79]Cong Lu, Philip J. Ball, Jack Parker-Holder, Michael A. Osborne, Stephen J. Roberts:
Revisiting Design Choices in Model-Based Offline Reinforcement Learning. CoRR abs/2110.04135 (2021) - [i78]Scott Alexander Cameron, Tyron Luke Cameron, Arnu Pretorius, Stephen J. Roberts:
Robust and Scalable SDE Learning: A Functional Perspective. CoRR abs/2110.05167 (2021) - [i77]Ivan Kiskin, Marianne Sinka, Adam D. Cobb, Waqas Rafique, Lawrence Wang, Davide Zilli, Benjamin Gutteridge, Rinita Dam, Theodoros Marinos, Yunpeng Li, Dickson Msaky, Emmanuel Kaindoa, Gerard Killeen, Eva Herreros-Moya, Kathy J. Willis, Stephen J. Roberts:
HumBugDB: A Large-scale Acoustic Mosquito Dataset. CoRR abs/2110.07607 (2021) - [i76]Shaan Desai, Marios Mattheakis, Hayden Joy, Pavlos Protopapas, Stephen J. Roberts:
One-Shot Transfer Learning of Physics-Informed Neural Networks. CoRR abs/2110.11286 (2021) - [i75]Kieran Wood, Sven Giegerich, Stephen J. Roberts, Stefan Zohren:
Trading with the Momentum Transformer: An Intelligent and Interpretable Architecture. CoRR abs/2112.08534 (2021) - 2020
- [j50]Jan-Peter Calliess, Stephen J. Roberts, Carl Edward Rasmussen, Jan M. Maciejowski:
Lazily Adapted Constant Kinky Inference for nonparametric regression and model-reference adaptive control. Autom. 122: 109216 (2020) - [j49]Ivan Kiskin, Davide Zilli, Yunpeng Li, Marianne Sinka, Kathy Willis, Stephen J. Roberts:
Bioacoustic detection with wavelet-conditioned convolutional neural networks. Neural Comput. Appl. 32(4): 915-927 (2020) - [c99]Arno Blaas, Andrea Patane, Luca Laurenti, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts:
Adversarial Robustness Guarantees for Classification with Gaussian Processes. AISTATS 2020: 3372-3382 - [c98]Matthew Willetts, Stephen J. Roberts, Chris C. Holmes:
Semi-Unsupervised Learning: Clustering and Classifying using Ultra-Sparse Labels. IEEE BigData 2020: 5286-5295 - [c97]Kyriakos Polymenakos, Luca Laurenti, Andrea Patane, Jan-Peter Calliess, Luca Cardelli, Marta Kwiatkowska, Alessandro Abate, Stephen J. Roberts:
Safety Guarantees for Iterative Predictions with Gaussian Processes. CDC 2020: 3187-3193 - [c96]Bernardo Pérez Orozco, Stephen J. Roberts:
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. ESANN 2020: 503-508 - [c95]Bingqing Liu, Ivan Kiskin, Stephen Roberts:
An Overview of Gaussian process Regression for Volatility Forecasting. ICAIIC 2020: 681-686 - [c94]Ivan Kiskin, Adam D. Cobb, Lawrence Wang, Stephen Roberts:
Humbug Zooniverse: A Crowd-Sourced Acoustic Mosquito Dataset. ICASSP 2020: 916-920 - [c93]Shuyu Lin, Ronald Clark, Robert Birke, Sandro Schönborn, Niki Trigoni, Stephen J. Roberts:
Anomaly Detection for Time Series Using VAE-LSTM Hybrid Model. ICASSP 2020: 4322-4326 - [c92]Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen J. Roberts:
Ready Policy One: World Building Through Active Learning. ICML 2020: 591-601 - [c91]Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts:
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. ICML 2020: 8276-8285 - [c90]Bryan Lim, Stefan Zohren, Stephen Roberts:
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. IJCNN 2020: 1-8 - [c89]Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes:
Explicit Regularisation in Gaussian Noise Injections. NeurIPS 2020 - [c88]Jack Parker-Holder, Vu Nguyen, Stephen J. Roberts:
Provably Efficient Online Hyperparameter Optimization with Population-Based Bandits. NeurIPS 2020 - [c87]Jack Parker-Holder, Aldo Pacchiano, Krzysztof Marcin Choromanski, Stephen J. Roberts:
Effective Diversity in Population Based Reinforcement Learning. NeurIPS 2020 - [c86]Kyriakos Polymenakos, Nikitas Rontsis, Alessandro Abate, Stephen J. Roberts:
SafePILCO: A Software Tool for Safe and Data-Efficient Policy Synthesis. QEST 2020: 18-26 - [i74]Ivan Kiskin, Adam D. Cobb, Lawrence Wang, Stephen Roberts:
HumBug Zooniverse: a crowd-sourced acoustic mosquito dataset. CoRR abs/2001.04733 (2020) - [i73]Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts:
Effective Diversity in Population-Based Reinforcement Learning. CoRR abs/2002.00632 (2020) - [i72]Bryan Lim, Stefan Zohren, Stephen Roberts:
Detecting Changes in Asset Co-Movement Using the Autoencoder Reconstruction Ratio. CoRR abs/2002.02008 (2020) - [i71]Jack Parker-Holder, Vu Nguyen, Stephen Roberts:
One-Shot Bayes Opt with Probabilistic Population Based Training. CoRR abs/2002.02518 (2020) - [i70]Philip J. Ball, Jack Parker-Holder, Aldo Pacchiano, Krzysztof Choromanski, Stephen Roberts:
Ready Policy One: World Building Through Active Learning. CoRR abs/2002.02693 (2020) - [i69]Alexander Camuto, Matthew Willetts, Brooks Paige, Chris C. Holmes, Stephen J. Roberts:
Learning Bijective Feature Maps for Linear ICA. CoRR abs/2002.07766 (2020) - [i68]Diego Granziol, Xingchen Wan, Stephen Roberts:
Iterate Averaging Helps: An Alternative Perspective in Deep Learning. CoRR abs/2003.01247 (2020) - [i67]Bernardo Pérez Orozco, Stephen J. Roberts:
Zero-shot and few-shot time series forecasting with ordinal regression recurrent neural networks. CoRR abs/2003.12162 (2020) - [i66]Jaleh Zand, Stephen Roberts:
Mixture Density Conditional Generative Adversarial Network Models (MD-CGAN). CoRR abs/2004.03797 (2020) - [i65]Shaan Desai, Stephen Roberts:
VIGN: Variational Integrator Graph Networks. CoRR abs/2004.13688 (2020) - [i64]Zihao Zhang, Stefan Zohren, Stephen Roberts:
Deep Learning for Portfolio Optimisation. CoRR abs/2005.13665 (2020) - [i63]Aldo Pacchiano, Philip J. Ball, Jack Parker-Holder, Krzysztof Choromanski, Stephen Roberts:
On Optimism in Model-Based Reinforcement Learning. CoRR abs/2006.11911 (2020) - [i62]Matthew Willetts, Xenia Miscouridou, Stephen J. Roberts, Chris C. Holmes:
Relaxed-Responsibility Hierarchical Discrete VAEs. CoRR abs/2007.07307 (2020) - [i61]Alexander Camuto, Matthew Willetts, Stephen J. Roberts, Chris C. Holmes, Tom Rainforth:
Towards a Theoretical Understanding of the Robustness of Variational Autoencoders. CoRR abs/2007.07365 (2020) - [i60]Alexander Camuto, Matthew Willetts, Umut Simsekli, Stephen J. Roberts, Chris C. Holmes:
Explicit Regularisation in Gaussian Noise Injections. CoRR abs/2007.07368 (2020) - [i59]Kyriakos Polymenakos, Nikitas Rontsis, Alessandro Abate, Stephen J. Roberts:
SafePILCO: a software tool for safe and data-efficient policy synthesis. CoRR abs/2008.03273 (2020) - [i58]Diego Granziol, Samuel Albanie, Xingchen Wan, Stephen J. Roberts:
Explaining the Adaptive Generalisation Gap. CoRR abs/2011.08181 (2020) - [i57]Daniel Poh, Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Building Cross-Sectional Systematic Strategies By Learning to Rank. CoRR abs/2012.07149 (2020)
2010 – 2019
- 2019
- [j48]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. Entropy 21(6): 551 (2019) - [j47]Jack K. Fitzsimons, AbdulRahman Al Ali, Michael A. Osborne, Stephen J. Roberts:
A General Framework for Fair Regression. Entropy 21(8): 741 (2019) - [j46]Glen Wright Colopy, Stephen J. Roberts, David A. Clifton:
Gaussian Processes for Personalized Interpretable Volatility Metrics in the Step-Down Ward. IEEE J. Biomed. Health Informatics 23(3): 949-959 (2019) - [j45]Zihao Zhang, Stefan Zohren, Stephen J. Roberts:
DeepLOB: Deep Convolutional Neural Networks for Limit Order Books. IEEE Trans. Signal Process. 67(11): 3001-3012 (2019) - [c85]Kyriakos Polymenakos, Alessandro Abate, Stephen J. Roberts:
Safe Policy Search Using Gaussian Process Models. AAMAS 2019: 1565-1573 - [c84]Richard Everett, Adam D. Cobb, Andrew Markham, Stephen J. Roberts:
Optimising Worlds to Evaluate and Influence Reinforcement Learning Agents. AAMAS 2019: 1943-1945 - [c83]Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen J. Roberts:
WiSE-ALE: Wide Sample Estimator for Aggregate Latent Embedding. DGS@ICLR 2019 - [c82]Ahsan S. Alvi, Bin Xin Ru, Jan-Peter Calliess, Stephen J. Roberts, Michael A. Osborne:
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. ICML 2019: 253-262 - [c81]Anup Aprem, Stephen J. Roberts:
Optimal Pricing In Black Box Producer-Consumer Stackelberg Games Using Revealed Preference Feedback. MLSP 2019: 1-6 - [i56]Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Recurrent Neural Filters: Learning Independent Bayesian Filtering Steps for Time Series Prediction. CoRR abs/1901.08096 (2019) - [i55]Matthew Willetts, Stephen J. Roberts, Christopher C. Holmes:
Semi-Unsupervised Learning with Deep Generative Models: Clustering and Classifying using Ultra-Sparse Labels. CoRR abs/1901.08560 (2019) - [i54]Ahsan S. Alvi, Bin Xin Ru, Jan Calliess, Stephen J. Roberts, Michael A. Osborne:
Asynchronous Batch Bayesian Optimisation with Improved Local Penalisation. CoRR abs/1901.10452 (2019) - [i53]Shuyu Lin, Ronald Clark, Robert Birke, Niki Trigoni, Stephen J. Roberts:
WiSE-VAE: Wide Sample Estimator VAE. CoRR abs/1902.06160 (2019) - [i52]Edwin Simpson, Steven Reece, Stephen J. Roberts:
Bayesian Heatmaps: Probabilistic Classification with Multiple Unreliable Information Sources. CoRR abs/1904.03063 (2019) - [i51]Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Enhancing Time Series Momentum Strategies Using Deep Neural Networks. CoRR abs/1904.04912 (2019) - [i50]Bryan Lim, Stefan Zohren, Stephen J. Roberts:
Population-based Global Optimisation Methods for Learning Long-term Dependencies with RNNs. CoRR abs/1905.09691 (2019) - [i49]Arno Blaas, Luca Laurenti, Andrea Patane, Luca Cardelli, Marta Kwiatkowska, Stephen J. Roberts:
Robustness Quantification for Classification with Gaussian Processes. CoRR abs/1905.11876 (2019) - [i48]Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes:
Disentangling Improves VAEs' Robustness to Adversarial Attacks. CoRR abs/1906.00230 (2019) - [i47]Diego Granziol, Bin Xin Ru, Stefan Zohren, Xiaowen Dong, Michael A. Osborne, Stephen J. Roberts:
MEMe: An Accurate Maximum Entropy Method for Efficient Approximations in Large-Scale Machine Learning. CoRR abs/1906.01101 (2019) - [i46]Bin Xin Ru, Ahsan S. Alvi, Vu Nguyen, Michael A. Osborne, Stephen J. Roberts:
Bayesian Optimisation over Multiple Continuous and Categorical Inputs. CoRR abs/1906.08878 (2019) - [i45]Favour M. Nyikosa, Michael A. Osborne, Stephen J. Roberts:
Adaptive Configuration Oracle for Online Portfolio Selection Methods. CoRR abs/1908.08258 (2019) - [i44]Shuyu Lin, Stephen J. Roberts, Niki Trigoni, Ronald Clark:
Balancing Reconstruction Quality and Regularisation in ELBO for VAEs. CoRR abs/1909.03765 (2019) - [i43]Matthew Willetts, Stephen J. Roberts, Chris C. Holmes:
Disentangling to Cluster: Gaussian Mixture Variational Ladder Autoencoders. CoRR abs/1909.11501 (2019) - [i42]Matthew Willetts, Alexander Camuto, Stephen J. Roberts, Chris C. Holmes:
Regularising Deep Networks with DGMs. CoRR abs/1909.11507 (2019) - [i41]Adam D. Cobb, Atilim Günes Baydin, Andrew Markham, Stephen J. Roberts:
Introducing an Explicit Symplectic Integration Scheme for Riemannian Manifold Hamiltonian Monte Carlo. CoRR abs/1910.06243 (2019) - [i40]Zihao Zhang, Stefan Zohren, Stephen J. Roberts:
Deep Reinforcement Learning for Trading. CoRR abs/1911.10107 (2019) - [i39]