Silvia Chiappa

According to our database1, Silvia Chiappa authored at least 37 papers between 2004 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Mind the Graph When Balancing Data for Fairness or Robustness.
CoRR, 2024

FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch.
CoRR, 2024

Pragmatic Fairness: Developing Policies with Outcome Disparity Control.
Proceedings of the Causal Learning and Reasoning, 2024

2023
DiscoGen: Learning to Discover Gene Regulatory Networks.
CoRR, 2023

Functional causal Bayesian optimization.
Proceedings of the Uncertainty in Artificial Intelligence, 2023

Transportability for Bandits with Data from Different Environments.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Additive Causal Bandits with Unknown Graph.
Proceedings of the International Conference on Machine Learning, 2023

Constrained Causal Bayesian Optimization.
Proceedings of the International Conference on Machine Learning, 2023

Learning to Induce Causal Structure.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Learning to Induce Causal Structure.
CoRR, 2022

Maintaining fairness across distribution shift: do we have viable solutions for real-world applications?
CoRR, 2022

Diagnosing failures of fairness transfer across distribution shift in real-world medical settings.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Statistical discrimination in learning agents.
CoRR, 2021

Prequential MDL for Causal Structure Learning with Neural Networks.
CoRR, 2021

Fairness with Continuous Optimal Transport.
CoRR, 2021

Asymptotically Best Causal Effect Identification with Multi-Armed Bandits.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
A General Approach to Fairness with Optimal Transport.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
Unsupervised Separation of Dynamics from Pixels.
CoRR, 2019

Meta-learning of Sequential Strategies.
CoRR, 2019

Causal Reasoning from Meta-reinforcement Learning.
CoRR, 2019

Wasserstein Fair Classification.
Proceedings of the Thirty-Fifth Conference on Uncertainty in Artificial Intelligence, 2019

Fairness in Machine Learning.
Proceedings of the Recent Trends in Learning From Data, 2019

Degenerate Feedback Loops in Recommender Systems.
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 2019

Path-Specific Counterfactual Fairness.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
A Causal Bayesian Networks Viewpoint on Fairness.
Proceedings of the Privacy and Identity Management. Fairness, Accountability, and Transparency in the Age of Big Data, 2018

2017
Recurrent Environment Simulators.
Proceedings of the 5th International Conference on Learning Representations, 2017

2014
Explicit-Duration Markov Switching Models.
Found. Trends Mach. Learn., 2014

2010
Movement extraction by detecting dynamics switches and repetitions.
Proceedings of the Advances in Neural Information Processing Systems 23: 24th Annual Conference on Neural Information Processing Systems 2010. Proceedings of a meeting held 6-9 December 2010, 2010

2009
A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection.
Proceedings of the SIAM International Conference on Data Mining, 2009

2008
Using Bayesian Dynamical Systems for Motion Template Libraries.
Proceedings of the Advances in Neural Information Processing Systems 21, 2008

A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation.
Proceedings of the Seventh International Conference on Machine Learning and Applications, 2008

2007
Bayesian Factorial Linear Gaussian State-Space Models for Biosignal Decomposition.
IEEE Signal Process. Lett., 2007

2006
EEG classification using generative independent component analysis.
Neurocomputing, 2006

Unified Inference for Variational Bayesian Linear Gaussian State-Space Models.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006

2005
generative independent component analysis for EEG classification.
Proceedings of the 13th European Symposium on Artificial Neural Networks, 2005

2004
HMM and IOHMM modeling of EEG rhythms for asynchronous BCI systems.
Proceedings of the 12th European Symposium on Artificial Neural Networks, 2004


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