Silvia Chiappa

57 papers A* 12A 5B 2C 2Journal 27Unranked 8

Year	Rank	Type	Title / Venue / Authors
2025	—	`conf`	BIG-Bench Extra Hard. ACL (1) Mehran Kazemi, Bahare Fatemi, Hritik Bansal, John Palowitch, Chrysovalantis Anastasiou, Sanket Vaibhav Mehta, Lalit K. Jain, Virginia Aglietti, Disha Jindal, Peter Chen, Nishanth Dikkala, Gladys Tyen, Xin Liu, Uri Shalit, Silvia Chiappa, Kate Olszewska, Yi Tay, Vinh Q. Tran, Quoc V. Le, Orhan Firat
2025	J	`jnl`	BIG-Bench Extra Hard. CoRR Mehran Kazemi, Bahare Fatemi, Hritik Bansal, John Palowitch, Chrysovalantis Anastasiou, Sanket Vaibhav Mehta, Kshitij Jain, Virginia Aglietti, Disha Jindal, Peter Chen, Nishanth Dikkala, Gladys Tyen, Xin Liu, Uri Shalit, Silvia Chiappa, Kate Olszewska, Yi Tay, Vinh Q. Tran, Quoc V. Le, Orhan Firat
2025	A	`ed.`	Conference on Uncertainty in Artificial Intelligence, Rio Othon Palace, Rio de Janeiro, Brazil, 21-25 July 2025. UAI Silvia Chiappa, Sara Magliacane
2025	A*	`conf`	FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. ICML Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
2024	J	`jnl`	FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. CoRR Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
2024	A*	`conf`	Mind the Graph When Balancing Data for Fairness or Robustness. NeurIPS Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa
2024	J	`jnl`	Mind the Graph When Balancing Data for Fairness or Robustness. CoRR Jessica Schrouff, Alexis Bellot, Amal Rannen-Triki, Alan Malek, Isabela Albuquerque, Arthur Gretton, Alexander D'Amour, Silvia Chiappa
2024	—	`conf`	Pragmatic Fairness: Developing Policies with Outcome Disparity Control. CLeaR Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva
2024	J	`jnl`	Prompting Strategies for Enabling Large Language Models to Infer Causation from Correlation. CoRR Eleni Sgouritsa, Virginia Aglietti, Yee Whye Teh, Arnaud Doucet, Arthur Gretton, Silvia Chiappa
2024	A*	`conf`	Towards Estimating Bounds on the Effect of Policies under Unobserved Confounding. NeurIPS Alexis Bellot, Silvia Chiappa
2023	A*	`conf`	Additive Causal Bandits with Unknown Graph. ICML Alan Malek, Virginia Aglietti, Silvia Chiappa
2023	J	`jnl`	Additive Causal Bandits with Unknown Graph. CoRR Alan Malek, Virginia Aglietti, Silvia Chiappa
2023	A*	`conf`	Constrained Causal Bayesian Optimization. ICML Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa
2023	J	`jnl`	Constrained Causal Bayesian Optimization. CoRR Virginia Aglietti, Alan Malek, Ira Ktena, Silvia Chiappa
2023	J	`jnl`	DiscoGen: Learning to Discover Gene Regulatory Networks. CoRR 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
2023	J	`jnl`	Functional Causal Bayesian Optimization. CoRR Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
2023	A	`conf`	Functional causal Bayesian optimization. UAI Limor Gultchin, Virginia Aglietti, Alexis Bellot, Silvia Chiappa
2023	A*	`conf`	Learning to Induce Causal Structure. ICLR 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
2023	J	`jnl`	Pragmatic Fairness: Developing Policies with Outcome Disparity Control. CoRR Limor Gultchin, Siyuan Guo, Alan Malek, Silvia Chiappa, Ricardo Silva
2023	A*	`conf`	Transportability for Bandits with Data from Different Environments. NeurIPS Alexis Bellot, Alan Malek, Silvia Chiappa
2022	A*	`conf`	Diagnosing failures of fairness transfer across distribution shift in real-world medical settings. NeurIPS 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
2022	J	`jnl`	Learning to Induce Causal Structure. CoRR Nan Rosemary Ke, Silvia Chiappa, Jane Wang, Jörg Bornschein, Theophane Weber, Anirudh Goyal, Matthew M. Botvinick, Michael Mozer, Danilo Jimenez Rezende
2022	J	`jnl`	Maintaining fairness across distribution shift: do we have viable solutions for real-world applications? CoRR Jessica Schrouff, Natalie Harris, Oluwasanmi Koyejo, Ibrahim 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
2022	A*	`conf`	Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness. AAAI Carolyn Ashurst, Ryan Carey, Silvia Chiappa, Tom Everitt
2022	J	`jnl`	Why Fair Labels Can Yield Unfair Predictions: Graphical Conditions for Introduced Unfairness. CoRR Carolyn Ashurst, Ryan Carey, Silvia Chiappa, Tom Everitt
2021	A*	`conf`	Asymptotically Best Causal Effect Identification with Multi-Armed Bandits. NeurIPS Alan Malek, Silvia Chiappa
2021	J	`jnl`	Fairness with Continuous Optimal Transport. CoRR Silvia Chiappa, Aldo Pacchiano
2021	J	`jnl`	Prequential MDL for Causal Structure Learning with Neural Networks. CoRR Jörg Bornschein, Silvia Chiappa, Alan Malek, Nan Rosemary Ke
2021	J	`jnl`	Statistical discrimination in learning agents. CoRR 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
2020	A*	`conf`	A General Approach to Fairness with Optimal Transport. AAAI Silvia Chiappa, Ray Jiang, Tom Stepleton, Aldo Pacchiano, Heinrich Jiang, John Aslanides
2020	J	`jnl`	Fairness in Machine Learning. CoRR Luca Oneto, Silvia Chiappa
2020	A	`ed.`	The 23rd International Conference on Artificial Intelligence and Statistics, AISTATS 2020, 26-28 August 2020, Online [Palermo, Sicily, Italy] AISTATS Silvia Chiappa, Roberto Calandra
2019	J	`jnl`	A Causal Bayesian Networks Viewpoint on Fairness. CoRR Silvia Chiappa, William S. Isaac
2019	J	`jnl`	Causal Reasoning from Meta-reinforcement Learning. CoRR Ishita Dasgupta, Jane X. Wang, Silvia Chiappa, Jovana Mitrovic, Pedro A. Ortega, David Raposo, Edward Hughes, Peter W. Battaglia, Matthew M. Botvinick, Zeb Kurth-Nelson
2019	C	`conf`	Degenerate Feedback Loops in Recommender Systems. AIES Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli
2019	J	`jnl`	Degenerate Feedback Loops in Recommender Systems. CoRR Ray Jiang, Silvia Chiappa, Tor Lattimore, András György, Pushmeet Kohli
2019	J	`jnl`	Explicit-Duration Markov Switching Models. CoRR Silvia Chiappa
2019	—	`conf`	Fairness in Machine Learning. INNSBDDL (Tutorials) Luca Oneto, Silvia Chiappa
2019	J	`jnl`	Meta-learning of Sequential Strategies. CoRR 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 M. Botvinick, Shane Legg
2019	A*	`conf`	Path-Specific Counterfactual Fairness. AAAI Silvia Chiappa
2019	J	`jnl`	Unsupervised Separation of Dynamics from Pixels. CoRR Silvia Chiappa, Ulrich Paquet
2019	A	`conf`	Wasserstein Fair Classification. UAI Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
2019	J	`jnl`	Wasserstein Fair Classification. CoRR Ray Jiang, Aldo Pacchiano, Tom Stepleton, Heinrich Jiang, Silvia Chiappa
2018	—	`conf`	A Causal Bayesian Networks Viewpoint on Fairness. Privacy and Identity Management Silvia Chiappa, William S. Isaac
2017	—	`conf`	Recurrent Environment Simulators. ICLR (Poster) Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
2017	J	`jnl`	Recurrent Environment Simulators. CoRR Silvia Chiappa, Sébastien Racanière, Daan Wierstra, Shakir Mohamed
2014	J	`jnl`	Explicit-Duration Markov Switching Models. Found. Trends Mach. Learn. Silvia Chiappa
2010	—	`conf`	Movement extraction by detecting dynamics switches and repetitions. NIPS Silvia Chiappa, Jan Peters
2009	A	`conf`	A Bayesian Approach to Graphy Regression with Relevant Subgraph Selection. SDM Silvia Chiappa, Hiroto Saigo, Koji Tsuda
2008	C	`conf`	A Bayesian Approach to Switching Linear Gaussian State-Space Models for Unsupervised Time-Series Segmentation. ICMLA Silvia Chiappa
2008	—	`conf`	Using Bayesian Dynamical Systems for Motion Template Libraries. NIPS Silvia Chiappa, Jens Kober, Jan Peters
2007	J	`jnl`	Bayesian Factorial Linear Gaussian State-Space Models for Biosignal Decomposition. IEEE Signal Process. Lett. Silvia Chiappa, David Barber
2006	—	`—`	Analysis and classification of EEG signals using probabilistic models for brain computer interfaces. Silvia Chiappa
2006	J	`jnl`	EEG classification using generative independent component analysis. Neurocomputing Silvia Chiappa, David Barber
2006	—	`conf`	Unified Inference for Variational Bayesian Linear Gaussian State-Space Models. NIPS David Barber, Silvia Chiappa
2005	B	`conf`	generative independent component analysis for EEG classification. ESANN Silvia Chiappa, David Barber
2004	B	`conf`	HMM and IOHMM modeling of EEG rhythms for asynchronous BCI systems. ESANN Silvia Chiappa, Nicolas Donckers, Samy Bengio, Frédéric Vrins