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Vidhi Lalchand
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Algorithmic trading review
P Treleaven, M Galas, V Lalchand
Communications of the ACM 56 (11), 76-85, 2013
1252013
Approximate Inference for Fully Bayesian Gaussian Process Regression
V Lalchand, CE Rasmussen
2nd Symposium on Advances in Approximate Bayesian Inference (NeurIPS 2019), 2019
24*2019
Physics-informed Gaussian process for online optimization of particle accelerators
A Hanuka, X Huang, J Shtalenkova, D Kennedy, A Edelen, VR Lalchand, ...
Physical Review Accelerators and Beams 24 (7), 2020
16*2020
Achieving Robustness to Aleatoric Uncertainty with Heteroscedastic Bayesian Optimisation
RR Griffiths, M Garcia-Ortegon, AA Aldrick, V Lalchand, AA Lee
Machine Learning: Science and Technology, 2021, 2019
92019
Marginalised Gaussian Processes with Nested Sampling
F Simpson, V Lalchand, CE Rasmussen
Advances in Neural Information Processing Systems (NeurIPS, 2021) 34, 2021
5*2021
Extracting more from boosted decision trees: A high energy physics case study
V Lalchand
2nd (NeurIPS, 2019) Workshop on Machine Learning and the Physical Sciences …, 2019
32019
Kernel Identification Through Transformers
F Simpson, I Davies, V Lalchand, A Vullo, N Durrande, C Rasmussen
Advances in Neural Information Processing Systems (NeurIPS, 2021) 34, 2021
22021
A Fast and Greedy Subset-of-Data (SoD) Scheme for Sparsification in Gaussian processes
V Lalchand, AC Faul
38th International Workshop on Bayesian Inference and Maximum Entropy …, 2018
12018
Generalised GPLVM with Stochastic Variational Inference
V Lalchand, A Ravuri, ND Lawrence
International Conference on Artificial Intelligence and Statistics, 7841-7864, 2022
2022
Gaussian Process Latent Variable Flows for Massively Missing Data
V Lalchand, A Ravuri, ND Lawrence
3rd Symposium on Advances in Approximate Bayesian Inference (AABI, 2020), 2020
2020
A meta-algorithm for classification using random recursive tree ensembles: A high energy physics application
V Lalchand
http://inspirehep.net/record/1776757, 2016
2016
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Articles 1–11