| Deep Bayesian Bandits Showdown: An Empirical Comparison of Bayesian Deep Networks for Thompson Sampling C Riquelme, G Tucker, J Snoek Sixth International Conference on Learning Representations, ICLR 2018., 2018 | 122 | 2018 |
| Dynamic Pricing in Ridesharing Platforms S Banerjee, R Johari, C Riquelme ACM SIGecom Exchanges 15 (1), 65-70, 2016 | 121* | 2016 |
| Pricing in ride-sharing platforms: A queueing-theoretic approach S Banerjee, R Johari, C Riquelme Proceedings of the Sixteenth ACM Conference on Economics and Computation …, 2015 | 116 | 2015 |
| Pricing in ride-share platforms: A queueing-theoretic approach C Riquelme, S Banerjee, R Johari Available at SSRN, 2015 | 32 | 2015 |
| Google research football: A novel reinforcement learning environment K Kurach, A Raichuk, P Stańczyk, M Zając, O Bachem, L Espeholt, ... Proceedings of the AAAI Conference on Artificial Intelligence 34 (04), 4501-4510, 2020 | 25 | 2020 |
| The visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... | 20 | 2019 |
| Human Interaction with Recommendation Systems S Schmit, C Riquelme The 21st International Conference on Artificial Intelligence and Statistics …, 2018 | 20 | 2018 |
| Online Active Linear Regression via Thresholding C Riquelme, R Johari, B Zhang AAAI-17, Thirty-First AAAI Conference on Artificial Intelligence., 2017 | 18 | 2017 |
| A large-scale study of representation learning with the visual task adaptation benchmark X Zhai, J Puigcerver, A Kolesnikov, P Ruyssen, C Riquelme, M Lucic, ... arXiv preprint arXiv:1910.04867, 2019 | 13 | 2019 |
| Practical and consistent estimation of f-divergences PK Rubenstein, O Bousquet, J Djolonga, C Riquelme, I Tolstikhin arXiv preprint arXiv:1905.11112, 2019 | 13 | 2019 |
| Learning Multifractal Structure in Large Networks AR Benson, C Riquelme, S Schmit Proceedings of the 20th ACM SIGKDD international conference on Knowledge …, 2014 | 13 | 2014 |
| The Beta-VAE's Implicit Prior MD Hoffman, C Riquelme, M Johnson Bayesian Deep Learning Workshop. Neural Information Processing Systems, NIPS …, 2017 | 12 | 2017 |
| Scalable transfer learning with expert models J Puigcerver, C Riquelme, B Mustafa, C Renggli, AS Pinto, S Gelly, ... arXiv preprint arXiv:2009.13239, 2020 | 6 | 2020 |
| Active Learning for Accurate Estimation of Linear Models C Riquelme, M Ghavamzadeh, A Lazaric Thirty-fourth International Conference on Machine Learning, ICML 2017., 2017 | 6 | 2017 |
| Pricing in ride-share platforms: A queueing-theoretic approach.(2015) S Banerjee, C Riquelme, R Johari Available at SSRN 2568258, 2015 | 6 | 2015 |
| On last-layer algorithms for classification: Decoupling representation from uncertainty estimation N Brosse, C Riquelme, A Martin, S Gelly, É Moulines arXiv preprint arXiv:2001.08049, 2020 | 2 | 2020 |
| Adaptive Temporal-Difference Learning for Policy Evaluation with Per-State Uncertainty Estimates. C Riquelme, H Penedones, D Vincent, H Maennel, S Gelly, TA Mann, ... NeurIPS, 2019 | 2* | 2019 |
| Human interaction with recommendation systems: On bias and exploration S Schmit, C Riquelme ArXiv e-prints, 2017 | 2 | 2017 |
| Google Research Football: A Novel Reinforcement Learning Environment A Raichuk, C Riquelme, D Vincent, K Kurach, L Espeholt, M Michalski, ... | 1 | 2019 |
| Failure modes of variational inference for decision making C Riquelme, M Johnson, M Hoffman Prediction and Generative Modeling in RL Workshop (AAMAS, ICML, IJCAI), 2018 | 1 | 2018 |
Siddhartha BanerjeeAssistant Professor, Operations Research, Cornell UniversityVerified email at cornell.edu
