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Amar Shah 0001
Person information
- affiliation: University of Cambridge, UK
Other persons with the same name
- Amar Shah 0002
— University of California, Berkeley, CA, USA
- Amar Shah 0003 — USAID
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2020 – today
- 2021
- [i8]Robert I. Citron, Peter Jenniskens, Christopher Watkins, Sravanthi Sinha, Amar Shah, Chedy Raïssi, Hadrien A. R. Devillepoix, Jim Albers:
Recovery of Meteorites Using an Autonomous Drone and Machine Learning. CoRR abs/2106.06523 (2021) - 2020
- [b1]Amar Shah:
Bayesian single- and multi-objective optimisation with nonparametric priors. University of Cambridge, UK, 2020 - [c13]Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemyslaw Mazur, Sean Micklethwaite, Nicolas Griffiths, Amar Shah, Alex Kendall:
Urban Driving with Conditional Imitation Learning. ICRA 2020: 251-257
2010 – 2019
- 2019
- [c12]Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah:
Learning to Drive in a Day. ICRA 2019: 8248-8254 - [i7]Jeffrey Hawke, Richard Shen, Corina Gurau, Siddharth Sharma, Daniele Reda, Nikolay Nikolov, Przemyslaw Mazur, Sean Micklethwaite, Nicolas Griffiths, Amar Shah, Alex Kendall:
Urban Driving with Conditional Imitation Learning. CoRR abs/1912.00177 (2019) - 2018
- [i6]Alex Kendall, Jeffrey Hawke, David Janz, Przemyslaw Mazur, Daniele Reda, John-Mark Allen, Vinh-Dieu Lam, Alex Bewley, Amar Shah:
Learning to Drive in a Day. CoRR abs/1807.00412 (2018) - 2017
- [c11]Rowan McAllister, Yarin Gal, Alex Kendall, Mark van der Wilk, Amar Shah, Roberto Cipolla, Adrian Weller:
Concrete Problems for Autonomous Vehicle Safety: Advantages of Bayesian Deep Learning. IJCAI 2017: 4745-4753 - 2016
- [c10]Martín Arjovsky, Amar Shah, Yoshua Bengio:
Unitary Evolution Recurrent Neural Networks. ICML 2016: 1120-1128 - [c9]Daniel Hernández-Lobato, José Miguel Hernández-Lobato, Amar Shah, Ryan P. Adams:
Predictive Entropy Search for Multi-objective Bayesian Optimization. ICML 2016: 1492-1501 - [c8]Amar Shah, Zoubin Ghahramani:
Pareto Frontier Learning with Expensive Correlated Objectives. ICML 2016: 1919-1927 - [c7]Amar Shah, Zoubin Ghahramani:
Markov Beta Processes for Time Evolving Dictionary Learning. UAI 2016 - 2015
- [c6]Amar Shah, David A. Knowles, Zoubin Ghahramani:
An Empirical Study of Stochastic Variational Inference Algorithms for the Beta Bernoulli Process. ICML 2015: 1594-1603 - [c5]Amar Shah, Zoubin Ghahramani:
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions. NIPS 2015: 3330-3338 - [i5]Amar Shah, David A. Knowles, Zoubin Ghahramani:
An Empirical Study of Stochastic Variational Algorithms for the Beta Bernoulli Process. CoRR abs/1506.08180 (2015) - [i4]Martín Arjovsky, Amar Shah, Yoshua Bengio:
Unitary Evolution Recurrent Neural Networks. CoRR abs/1511.06464 (2015) - [i3]Amar Shah, Zoubin Ghahramani:
Parallel Predictive Entropy Search for Batch Global Optimization of Expensive Objective Functions. CoRR abs/1511.07130 (2015) - 2014
- [c4]Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani:
Student-t Processes as Alternatives to Gaussian Processes. AISTATS 2014: 877-885 - [c3]Philip Woodall
, Torben Jess, Mark Harrison, Duncan C. McFarlane, Amar Shah, William E. Krechel, Eric Nicks:
A framework for detecting unnecessary industrial data in ETL processes. INDIN 2014: 472-476 - [i2]Amar Shah, Andrew Gordon Wilson, Zoubin Ghahramani:
Student-t Processes as Alternatives to Gaussian Processes. CoRR abs/1402.4306 (2014) - 2013
- [c2]Tomoharu Iwata, Amar Shah, Zoubin Ghahramani:
Discovering latent influence in online social activities via shared cascade poisson processes. KDD 2013: 266-274 - [c1]Amar Shah, Zoubin Ghahramani:
Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. UAI 2013 - [i1]Amar Shah, Zoubin Ghahramani:
Determinantal Clustering Processes - A Nonparametric Bayesian Approach to Kernel Based Semi-Supervised Clustering. CoRR abs/1309.6862 (2013)
Coauthor Index
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