Silvia Chiappa

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 38

Top Topics

Causal Structure

Monte Carlo Sampling

Top Venues

Publications

Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva
Pragmatic Fairness: Developing Policies with Outcome Disparity Control. CLeaR (2024)
Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa
Mind the Graph When Balancing Data for Fairness or Robustness. CoRR (2024)
Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. CoRR (2024)
Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa
Constrained Causal Bayesian Optimization. ICML (2023)
Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
Functional causal Bayesian optimization. UAI (2023)
Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva
Pragmatic Fairness: Developing Policies with Outcome Disparity Control. CoRR (2023)
Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa
Constrained Causal Bayesian Optimization. CoRR (2023)
Alexis Bellot, Alan Malek, Silvia Chiappa
Transportability for Bandits with Data from Different Environments. NeurIPS (2023)
Nan Rosemary Ke, Silvia Chiappa, Jane X. Wang, Jörg Bornschein, Anirudh Goyal, Mélanie Rey, Theophane Weber, Matthew M. Botvinick, Michael Curtis Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. ICLR (2023)
Alan Malek, Virginia Aglietti, Silvia Chiappa
Additive Causal Bandits with Unknown Graph. CoRR (2023)
Alan Malek, Virginia Aglietti, Silvia Chiappa
Additive Causal Bandits with Unknown Graph. ICML (2023)
Nan Rosemary Ke, Sara-Jane Dunn, Jörg Bornschein, Silvia Chiappa, Mélanie Rey, Jean-Baptiste Lespiau, Albin Cassirer, Jane X. Wang, Theophane Weber, David G. T. Barrett, Matthew M. Botvinick, Anirudh Goyal, Michael Mozer, Danilo J. Rezende
DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR (2023)
Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
Functional Causal Bayesian Optimization. CoRR (2023)
Carolyn Ashurst, Ryan Carey, Silvia Chiappa, Tom Everitt
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness. CoRR (2022)
Carolyn Ashurst, Ryan Carey, Silvia Chiappa, Tom Everitt
Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness. AAAI (2022)
Jessica Schrouff, Natalie Harris, Sanmi Koyejo, Ibrahim M. Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alexander Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour
Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS (2022)
Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim Alabdulmohsin, Eva Schnider, Krista Opsahl-Ong, Alex Brown, Subhrajit Roy, Diana Mincu, Christina Chen, Awa Dieng, Yuan Liu, Vivek Natarajan, Alan Karthikesalingam, Katherine A. Heller, Silvia Chiappa, Alexander D'Amour
Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR (2022)
Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
Learning to Induce Causal Structure. CoRR (2022)
Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke
Prequential MDL for Causal Structure Learning with Neural Networks. CoRR (2021)
Alan Malek, Silvia Chiappa
Asymptotically Best Causal Effect Identification with Multi-Armed Bandits. NeurIPS (2021)
Edgar A. Duéñez-Guzmán, Kevin R. McKee, Yiran Mao, Ben Coppin, Silvia Chiappa, Alexander Sasha Vezhnevets, Michiel A. Bakker, Yoram Bachrach, Suzanne Sadedin, William Isaac, Karl Tuyls, Joel Z. Leibo
Statistical discrimination in learning agents. CoRR (2021)
Silvia Chiappa, Aldo Pacchiano
Fairness with Continuous Optimal Transport. CoRR (2021)
Luca Oneto, Silvia Chiappa
Fairness in Machine Learning. CoRR (2020)
Silvia Chiappa, Ray Jiang, Tom Stepleton, Aldo Pacchiano, Heinrich Jiang, John Aslanides
A General Approach to Fairness with Optimal Transport. AAAI (2020)
Silvia Chiappa
Path-Specific Counterfactual Fairness. AAAI (2019)
Silvia Chiappa
Explicit-Duration Markov Switching Models. CoRR (2019)
Silvia Chiappa, William S. Isaac
A Causal Bayesian Networks Viewpoint on Fairness. CoRR (2019)
Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli
Degenerate Feedback Loops in Recommender Systems. AIES (2019)
Silvia Chiappa, Ulrich Paquet
Unsupervised Separation of Dynamics from Pixels. CoRR (2019)
Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew Botvinick, Zeb Kurth-Nelson
Causal Reasoning from Meta-reinforcement Learning. CoRR (2019)
Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
Wasserstein Fair Classification. CoRR (2019)
Luca Oneto, Silvia Chiappa
Fairness in Machine Learning. INNSBDDL (Tutorials) (2019)
Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
Wasserstein Fair Classification. UAI (2019)
Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli
Degenerate Feedback Loops in Recommender Systems. CoRR (2019)
Pedro A. Ortega, Jane X. Wang, Mark Rowland, Tim Genewein, Zeb Kurth-Nelson, Razvan Pascanu, Nicolas Heess, Joel Veness, Alexander Pritzel, Pablo Sprechmann, Siddhant M. Jayakumar, Tom McGrath, Kevin J. Miller, Mohammad Gheshlaghi Azar, Ian Osband, Neil C. Rabinowitz, András György, Silvia Chiappa, Simon Osindero, Yee Whye Teh, Hado van Hasselt, Nando de Freitas, Matthew Botvinick, Shane Legg
Meta-learning of Sequential Strategies. CoRR (2019)
Silvia Chiappa, William S. Isaac
A Causal Bayesian Networks Viewpoint on Fairness. Privacy and Identity Management (2018)
Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
Recurrent Environment Simulators. CoRR (2017)
Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
Recurrent Environment Simulators. ICLR (Poster) (2017)
Silvia Chiappa
Explicit-Duration Markov Switching Models. Found. Trends Mach. Learn. 7 (6) (2014)
Silvia Chiappa, Jan Peters
Movement extraction by detecting dynamics switches and repetitions. NIPS (2010)
Silvia Chiappa, Hiroto Saigo, Koji Tsuda
A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection. SDM (2009)
Silvia Chiappa
A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation. ICMLA (2008)
Silvia Chiappa, Jens Kober, Jan Peters
Using Bayesian Dynamical Systems for Motion Template Libraries. NIPS (2008)
Silvia Chiappa, David Barber
Bayesian Factorial Linear Gaussian State-Space Models for Biosignal Decomposition. IEEE Signal Process. Lett. 14 (4) (2007)
Silvia Chiappa, David Barber
EEG classification using generative independent component analysis. Neurocomputing 69 (7-9) (2006)
David Barber, Silvia Chiappa
Unified Inference for Variational Bayesian Linear Gaussian State-Space Models. NIPS (2006)
Silvia Chiappa, David Barber
generative independent component analysis for EEG classification. ESANN (2005)
Silvia Chiappa, Nicolas Donckers, Samy Bengio, Frédéric Vrins
HMM and IOHMM modeling of EEG rhythms for asynchronous BCI systems. ESANN (2004)