James Robert Lloyd

University of Cambridge — United Kingdom

Computer Science · Physical Sciences

11h-index1.1kcitations15works0.02yr avg
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Research Topics

Gaussian Processes and Bayesian Inference(9), Time Series Analysis and Forecasting(5), Neural Networks and Applications(4), Machine Learning and Data Classification(3), Domain Adaptation and Few-Shot Learning(2)

Publications15 total

The Automatic Statistician
˜The œSpringer series on challenges in machine learning·2019· 48 citedOpen Access
One-Shot Learning in Discriminative Neural Networks
arXiv (Cornell University)·2017· 2 citedOpen Access
One-Shot Learning in Discriminative Neural Networks
Apollo (University of Cambridge)·2017· 3 citedOpen Access
A brief Review of the ChaLearn AutoML Challenge: Any-time Any-dataset Learning without Human Intervention
SPIRE - Sciences Po Institutional REpository·2016· 59 cited
Statistical model criticism using kernel two sample tests
Neural Information Processing Systems·2015· 64 cited
Unsupervised Many-to-Many Object Matching for Relational Data
IEEE Transactions on Pattern Analysis and Machine Intelligence·2015· 12 cited
Automatic Construction and Natural-Language Description of Nonparametric Regression Models
Proceedings of the AAAI Conference on Artificial Intelligence·2014· 124 citedOpen Access
Automatic Construction and Natural-Language Description of Nonparametric Regression Models
DSpace@MIT (Massachusetts Institute of Technology)·2014· 82 citedOpen Access
Automatic Construction and Natural-Language Description of Nonparametric\n Regression Models
arXiv (Cornell University)·2014· 3 citedOpen Access
GEFCom2012 hierarchical load forecasting: Gradient boosting machines and Gaussian processes
International Journal of Forecasting·2013· 109 cited
Gaussian Process Conditional Copulas with Applications to Financial Time\n Series
arXiv (Cornell University)·2013· 2 citedOpen Access
Gaussian Process Conditional Copulas with Applications to Financial Time Series
LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)·2013· 11 citedOpen Access
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
DSpace@MIT (Massachusetts Institute of Technology)·2013· 191 citedOpen Access
Structure Discovery in Nonparametric Regression through Compositional Kernel Search
arXiv (Cornell University)·2013· 273 citedOpen Access
Random function priors for exchangeable arrays with applications to graphs and relational data
2012· 90 cited

Frequent Co-authors

Zoubin Ghahramani(9), David Duvenaud(5), Roger Grosse(5), Joshua B. Tenenbaum(5), Zoubin Ghahramani(2), José Miguel Hernández-Lobato(2), Daniel Hernández-Lobato(2), Jordan Burgess(2), Peter Orbanz(1), Daniel M. Roy(1), Isabelle Guyon(1), Imad Chaabane(1), Hugo Jair Escalante(1), Sérgio Escalera(1), Damir Jajetic(1), Núria Macià(1), Bisakha Ray(1), Łukasz Romaszko(1), Michèle Sébag(1), Alexander Statnikov(1)