default search action
Google
Google Scholar
Semantic Scholar
Internet Archive Scholar
CiteSeerX
ORCIDRicardo Silva 0001
Person information
- affiliation: University College London, Department of Statistical Science, London, UK
- affiliation: The Alan Turing Institute, London, UK
- affiliation (PhD 2005): Carnegie Mellon University, Machine Learning Department, Pittsburgh, PA, USA
Other persons with the same name
- Ricardo Silva — disambiguation page
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
2020 – today
- 2024
[c27]Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva:
Pragmatic Fairness: Developing Policies with Outcome Disparity Control. CLeaR 2024: 243-264- [c26]Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang:
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models. NeurIPS 2024 - [c25]Jialin Yu, Andreas Koukorinis, Nicolò Colombo, Yuchen Zhu, Ricardo Silva:
Structured Learning of Compositional Sequential Interventions. NeurIPS 2024 - [c24]David S. Watson, Jordan Penn, Lee M. Gunderson, Gecia Bravo Hermsdorff, Afsaneh Mastouri, Ricardo Silva:
Bounding causal effects with leaky instruments. UAI 2024: 3689-3710 - [i31]Ricardo Silva:
Counterfactual Fairness Is Not Demographic Parity, and Other Observations. CoRR abs/2402.02663 (2024) - [i30]David S. Watson, Jordan Penn
, Lee M. Gunderson, Gecia Bravo Hermsdorff, Afsaneh Mastouri, Ricardo Silva:
Bounding Causal Effects with Leaky Instruments. CoRR abs/2404.04446 (2024) - [i29]Jialin Yu, Andreas Koukorinis, Nicolò Colombo, Yuchen Zhu, Ricardo Silva:
Structured Learning of Compositional Sequential Interventions. CoRR abs/2406.05745 (2024) - [i28]Jialin Yu, Yuxiang Zhou, Yulan He, Nevin L. Zhang, Ricardo Silva:
Fine-Tuning Pre-trained Language Models for Robust Causal Representation Learning. CoRR abs/2410.14375 (2024) - [i27]Kaican Li, Weiyan Xie, Yongxiang Huang, Didan Deng, Lanqing Hong, Zhenguo Li, Ricardo Silva, Nevin L. Zhang:
Dual Risk Minimization: Towards Next-Level Robustness in Fine-tuning Zero-Shot Models. CoRR abs/2411.19757 (2024) - 2023
- [c23]Kirtan Padh, Jakob Zeitler, David S. Watson, Matt J. Kusner, Ricardo Silva, Niki Kilbertus:
Stochastic Causal Programming for Bounding Treatment Effects. CLeaR 2023: 142-176 - [c22]Gecia Bravo Hermsdorff, David S. Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva:
Intervention Generalization: A View from Factor Graph Models. NeurIPS 2023 - [i26]Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva:
Pragmatic Fairness: Developing Policies with Outcome Disparity Control. CoRR abs/2301.12278 (2023) - [i25]Aengus Lynch, Gbètondji J.-S. Dovonon, Jean Kaddour, Ricardo Silva:
Spawrious: A Benchmark for Fine Control of Spurious Correlation Biases. CoRR abs/2303.05470 (2023) - [i24]Gecia Bravo Hermsdorff, David S. Watson, Jialin Yu, Jakob Zeitler, Ricardo Silva:
Intervention Generalization: A View from Factor Graph Models. CoRR abs/2306.04027 (2023) - 2022
- [j5]Alessio Pagani, Zhuangkun Wei, Ricardo Silva, Weisi Guo:
Neural Network Approximation of Graph Fourier Transform for Sparse Sampling of Networked Dynamics. ACM Trans. Internet Techn. 22(1): 21:1-21:18 (2022) - [c21]Jacobo Roa-Vicens, Yao Lei Xu, Ricardo Silva, Danilo P. Mandic:
Graph and tensor-train recurrent neural networks for high-dimensional models of limit order books. ICAIF 2022: 207-213 - [c20]Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner:
When Do Flat Minima Optimizers Work? NeurIPS 2022 - [c19]David S. Watson, Ricardo Silva:
Causal discovery under a confounder blanket. UAI 2022: 2096-2106 - [c18]Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva:
Causal inference with treatment measurement error: a nonparametric instrumental variable approach. UAI 2022: 2414-2424 - [i23]Jean Kaddour, Linqing Liu, Ricardo Silva, Matt J. Kusner:
Questions for Flat-Minima Optimization of Modern Neural Networks. CoRR abs/2202.00661 (2022) - [i22]Kirtan Padh, Jakob Zeitler, David S. Watson, Matt J. Kusner, Ricardo Silva, Niki Kilbertus:
Stochastic Causal Programming for Bounding Treatment Effects. CoRR abs/2202.10806 (2022) - [i21]Jakob Zeitler, Ricardo Silva:
The Causal Marginal Polytope for Bounding Treatment Effects. CoRR abs/2202.13851 (2022) - [i20]David S. Watson, Ricardo Silva:
Causal discovery under a confounder blanket. CoRR abs/2205.05715 (2022) - [i19]Yuchen Zhu, Limor Gultchin, Arthur Gretton, Matt J. Kusner, Ricardo Silva:
Causal Inference with Treatment Measurement Error: A Nonparametric Instrumental Variable Approach. CoRR abs/2206.09186 (2022) - [i18]Jean Kaddour, Aengus Lynch, Qi Liu, Matt J. Kusner, Ricardo Silva:
Causal Machine Learning: A Survey and Open Problems. CoRR abs/2206.15475 (2022) - 2021
- [c17]Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva:
Operationalizing Complex Causes: A Pragmatic View of Mediation. ICML 2021: 3875-3885 - [c16]Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet:
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. ICML 2021: 7512-7523 - [c15]Jean Kaddour, Yuchen Zhu, Qi Liu, Matt J. Kusner, Ricardo Silva:
Causal Effect Inference for Structured Treatments. NeurIPS 2021: 24841-24854 - [i17]Afsaneh Mastouri, Yuchen Zhu, Limor Gultchin, Anna Korba, Ricardo Silva, Matt J. Kusner, Arthur Gretton, Krikamol Muandet:
Proximal Causal Learning with Kernels: Two-Stage Estimation and Moment Restriction. CoRR abs/2105.04544 (2021) - [i16]Jean Kaddour, Qi Liu, Yuchen Zhu, Matt J. Kusner, Ricardo Silva:
Graph Intervention Networks for Causal Effect Estimation. CoRR abs/2106.01939 (2021) - [i15]Limor Gultchin, David S. Watson, Matt J. Kusner, Ricardo Silva:
Operationalizing Complex Causes: A Pragmatic View of Mediation. CoRR abs/2106.05074 (2021) - 2020
- [c14]Limor Gultchin, Matt J. Kusner, Varun Kanade, Ricardo Silva:
Differentiable Causal Backdoor Discovery. AISTATS 2020: 3970-3979 - [c13]Niki Kilbertus, Matt J. Kusner, Ricardo Silva:
A Class of Algorithms for General Instrumental Variable Models. NeurIPS 2020 - [c12]Pawel M. Chilinski, Ricardo Silva:
Neural Likelihoods via Cumulative Distribution Functions. UAI 2020: 420-429 - [i14]Alessio Pagani, Zhuangkun Wei, Ricardo Silva, Weisi Guo:
Neural Network Approximation of Graph Fourier Transforms for Sparse Sampling of Networked Flow Dynamics. CoRR abs/2002.05508 (2020) - [i13]Limor Gultchin, Matt J. Kusner, Varun Kanade, Ricardo Silva:
Differentiable Causal Backdoor Discovery. CoRR abs/2003.01461 (2020) - [i12]Niki Kilbertus, Matt J. Kusner, Ricardo Silva:
A Class of Algorithms for General Instrumental Variable Models. CoRR abs/2006.06366 (2020)
2010 – 2019
- 2019
- [j4]William G. Dixon, Anna L. Beukenhorst, Belay Birlie Yimer, Louise Cook, Antonio Gasparrini, Tal El-Hay, Bruce Hellman, Ben James, Ana M. Vicedo-Cabrera, Malcolm Maclure, Ricardo Silva, John D. Ainsworth, Huai Leng Pisaniello, Thomas A. House, Mark Lunt, Carolyn Gamble, Caroline Sanders, David M. Schultz, Jamie C. Sergeant, John McBeth:
How the weather affects the pain of citizen scientists using a smartphone app. npj Digit. Medicine 2 (2019) - [c11]Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva:
Making Decisions that Reduce Discriminatory Impacts. ICML 2019: 3591-3600 - [c10]Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva:
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. UAI 2019: 616-626 - [e4]Amir Globerson, Ricardo Silva:
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, UAI 2019, Tel Aviv, Israel, July 22-25, 2019. Proceedings of Machine Learning Research 115, AUAI Press 2019 [contents] - [i11]Jacobo Roa-Vicens, Cyrine Chtourou, Angelos Filos, Francisco Rullan, Yarin Gal, Ricardo Silva:
Towards Inverse Reinforcement Learning for Limit Order Book Dynamics. CoRR abs/1906.04813 (2019) - [i10]Niki Kilbertus, Philip J. Ball, Matt J. Kusner, Adrian Weller, Ricardo Silva:
The Sensitivity of Counterfactual Fairness to Unmeasured Confounding. CoRR abs/1907.01040 (2019) - [i9]Nicolò Colombo, Ricardo Silva, Soong Moon Kang, Arthur Gretton:
Counterfactual Distribution Regression for Structured Inference. CoRR abs/1908.07193 (2019) - [i8]Jacobo Roa-Vicens, Yuanbo Wang, Virgile Mison, Yarin Gal, Ricardo Silva:
Adversarial recovery of agent rewards from latent spaces of the limit order book. CoRR abs/1912.04242 (2019) - 2018
- [j3]Gavin A. Whitaker, Ricardo Silva, Daniel Edwards:
Visualizing a Team's Goal Chances in Soccer from Attacking Events: A Bayesian Inference Approach. Big Data 6(4): 271-290 (2018) - [c9]Yin Cheng Ng, Nicolò Colombo, Ricardo Silva:
Bayesian Semi-supervised Learning with Graph Gaussian Processes. NeurIPS 2018: 1690-1701 - [e3]Amir Globerson, Ricardo Silva:
Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence, UAI 2018, Monterey, California, USA, August 6-10, 2018. AUAI Press 2018 [contents] - [i7]Jean-Baptiste Regli, Ricardo Silva:
Alpha-Beta Divergence For Variational Inference. CoRR abs/1805.01045 (2018) - [i6]Joshua R. Loftus, Chris Russell, Matt J. Kusner, Ricardo Silva:
Causal Reasoning for Algorithmic Fairness. CoRR abs/1805.05859 (2018) - [i5]Matt J. Kusner, Chris Russell, Joshua R. Loftus, Ricardo Silva:
Causal Interventions for Fairness. CoRR abs/1806.02380 (2018) - [i4]Yin Cheng Ng, Ricardo Silva:
Bayesian Semi-supervised Learning with Graph Gaussian Processes. CoRR abs/1809.04379 (2018) - [i3]Pawel M. Chilinski, Ricardo Silva:
Neural Likelihoods via Cumulative Distribution Functions. CoRR abs/1811.00974 (2018) - 2017
- [j2]Ricardo Silva, Shohei Shimizu:
Learning Instrumental Variables with Structural and Non-Gaussianity Assumptions. J. Mach. Learn. Res. 18: 120:1-120:49 (2017) - [c8]Rafael Augusto Ferreira do Carmo, Soong Moon Kang, Ricardo Silva:
Visualization of Topic-Sentiment Dynamics in Crowdfunding Projects. IDA 2017: 40-51 - [c7]Nicolò Colombo, Ricardo Silva, Soong Moon Kang:
Tomography of the London Underground: a Scalable Model for Origin-Destination Data. NIPS 2017: 3062-3073 - [c6]Matt J. Kusner, Joshua R. Loftus, Chris Russell, Ricardo Silva:
Counterfactual Fairness. NIPS 2017: 4066-4076 - [c5]Chris Russell, Matt J. Kusner, Joshua R. Loftus, Ricardo Silva:
When Worlds Collide: Integrating Different Counterfactual Assumptions in Fairness. NIPS 2017: 6414-6423 - [e2]Frederick Eberhardt, Elias Bareinboim, Marloes H. Maathuis, Joris M. Mooij, Ricardo Silva:
Proceedings of the UAI 2016 Workshop on Causation: Foundation to Application co-located with the 32nd Conference on Uncertainty in Artificial Intelligence (UAI 2016), Jersey City, USA, June 29, 2016. CEUR Workshop Proceedings 1792, CEUR-WS.org 2017 [contents] - [r1]Ricardo Silva:
Causality. Encyclopedia of Machine Learning and Data Mining 2017: 194-202 - [i2]Matt J. Kusner, Joshua R. Loftus, Chris Russell, Ricardo Silva:
Counterfactual Fairness. CoRR abs/1703.06856 (2017) - [i1]Yin Cheng Ng, Ricardo Silva:
A Dynamic Edge Exchangeable Model for Sparse Temporal Networks. CoRR abs/1710.04008 (2017) - 2016
- [j1]Ricardo Silva, Robin J. Evans:
Causal Inference through a Witness Protection Program. J. Mach. Learn. Res. 17: 56:1-56:53 (2016) - [c4]Ricardo Silva:
Observational-Interventional Priors for Dose-Response Learning. NIPS 2016: 1561-1569 - [c3]Yin Cheng Ng, Pawel M. Chilinski, Ricardo Silva:
Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages. NIPS 2016: 4044-4052 - 2015
- [e1]Ricardo Silva, Ilya Shpitser, Robin J. Evans, Jonas Peters, Tom Claassen:
Proceedings of the UAI 2015 Workshop on Advances in Causal Inference co-located with the 31st Conference on Uncertainty in Artificial Intelligence (UAI 2015), Amsterdam, The Netherlands, July 16, 2015. CEUR Workshop Proceedings 1504, CEUR-WS.org 2015 [contents] - 2014
- [c2]Ricardo Silva, Robin J. Evans:
Causal Inference through a Witness Protection Program. NIPS 2014: 298-306 - 2012
- [c1]Ricardo Silva:
Latent Composite Likelihood Learning for the Structured Canonical Correlation Model. UAI 2012: 765-774
Coauthor Index
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from 
to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the 
of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from 
, 
, and 
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from 
.
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2025-05-18 20:28 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by:
