Ricardo Silva
Identifiers
- name variant Ricardo Silva 0.60 · backfill
Papers (28)
- IV-ICL: Bounding Causal Effects with Instrumental Variables via In-Context Learning cs.LG · 2026 · author #4
- Correcting heterogeneous diagnostic bias when developing clinical prediction models using causal hidden Markov models stat.AP · 2026 · author #2
- Causal Fine-Tuning under Latent Confounded Shift cs.LG · 2024 · author #9
- Sharing and Learning Alloy on the Web cs.CY · 2019 · author #5
- Towards Inverse Reinforcement Learning for Limit Order Book Dynamics cs.LG · 2019 · author #6
- Bayesian Semi-supervised Learning with Graph Gaussian Processes cs.LG · 2018 · author #3
- Ethical Implications of Social Internet of Vehicles Systems cs.CY · 2018 · author #1
- Causal Interventions for Fairness stat.ML · 2018 · author #4
- Causal Reasoning for Algorithmic Fairness cs.AI · 2018 · author #4
- Alpha-Beta Divergence For Variational Inference stat.ML · 2018 · author #2
- Modeling goal chances in soccer: a Bayesian inference approach stat.AP · 2018 · author #2
- A Dynamic Edge Exchangeable Model for Sparse Temporal Networks stat.ML · 2017 · author #2
- Counterfactual Fairness stat.ML · 2017 · author #4
- Scaling Factorial Hidden Markov Models: Stochastic Variational Inference without Messages stat.ML · 2016 · author #3
- Observational-Interventional Priors for Dose-Response Learning stat.ML · 2016 · author #1
- Bayesian Inference in Cumulative Distribution Fields stat.ML · 2015 · author #1
- Learning Instrumental Variables with Non-Gaussianity Assumptions: Theoretical Limitations and Practical Algorithms stat.ML · 2015 · author #1
- Gaussian Process Structural Equation Models with Latent Variables cs.LG · 2014 · author #1
- Causal Inference through a Witness Protection Program stat.ML · 2014 · author #1
- Flexible sampling of discrete data correlations without the marginal distributions stat.ML · 2013 · author #2
- Learning Measurement Models for Unobserved Variables cs.LG · 2012 · author #1
- Latent Composite Likelihood Learning for the Structured Canonical Correlation Model stat.ML · 2012 · author #1
- Bayesian Inference for Gaussian Mixed Graph Models stat.ME · 2012 · author #1
- Mixed Cumulative Distribution Networks stat.ML · 2010 · author #1
- Gaussian Process Structural Equation Models with Latent Variables cs.LG · 2010 · author #1
- Measuring Latent Causal Structure cs.LG · 2010 · author #1
- Ranking relations using analogies in biological and information networks stat.ME · 2009 · author #1
- On estimating covariances between many assets with histories of highly variable length stat.ME · 2007 · author #3
Mentions
- 1212.2516 #1 · backfill · confidence 0.70 Ricardo Silva
- 1210.4905 #1 · backfill · confidence 0.70 Ricardo Silva
- 1206.6874 #1 · backfill · confidence 0.70 Ricardo Silva
- 1008.5386 #1 · backfill · confidence 0.70 Ricardo Silva
- 1002.4802 #1 · backfill · confidence 0.70 Ricardo Silva
- 1001.1079 #1 · backfill · confidence 0.70 Ricardo Silva
- 0912.5193 #1 · backfill · confidence 0.70 Ricardo Silva
- 0710.5837 #3 · backfill · confidence 0.70 Ricardo Silva
Frequent Coauthors
- Chris Russell 3 shared papers
- Joshua R. Loftus 3 shared papers
- Matt J. Kusner 3 shared papers
- Robert B. Gramacy 3 shared papers
- Yin Cheng Ng 3 shared papers
- Zoubin Ghahramani 2 shared papers
- Alcino Cunha 1 shared papers
- Alfredo Kalaitzis 1 shared papers
- Ana C. R. Paiva 1 shared papers
- Angelos Filos 1 shared papers
- Brian McMillan 1 shared papers
- Charles Blundell 1 shared papers
- Clark Glymour 1 shared papers
- Cyrine Chtourou 1 shared papers
- Daniel Edwards 1 shared papers
- Daniel Silva 1 shared papers
- Edoardo M. Airoldi 1 shared papers
- Francisco Rullan 1 shared papers
- Gavin A. Whitaker 1 shared papers
- Hamidreza Kamkari 1 shared papers