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Sahra Ghalebikesabi
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2020 – today
- 2024
- [j1]Fabian Falck, Xuan Zhu, Sahra Ghalebikesabi
, Matthias Kormaksson, Marc Vandemeulebroecke, Cong Zhang, Ruvie Martin, Stephen Gardiner
, Chun Hei Kwok
, Dominique M. West, Luis A. Santos
, Chengeng Tian
, Yu Pang, Aimee Readie, Gregory Ligozio, Kunal K. Gandhi, Thomas E. Nichols
, Ann-Marie Mallon, Luke J. Kelly
, David Ohlssen, George Nicholson
:
A framework for longitudinal latent factor modelling of treatment response in clinical trials with applications to Psoriatic Arthritis and Rheumatoid Arthritis. J. Biomed. Informatics 154: 104641 (2024) - [i10]Lucile Ter-Minassian, Sahra Ghalebikesabi, Karla Diaz-Ordaz, Chris C. Holmes:
Explainable AI for survival analysis: a median-SHAP approach. CoRR abs/2402.00072 (2024) - [i9]Eugene Bagdasaryan, Ren Yi, Sahra Ghalebikesabi, Peter Kairouz, Marco Gruteser, Sewoong Oh, Borja Balle, Daniel Ramage:
Air Gap: Protecting Privacy-Conscious Conversational Agents. CoRR abs/2405.05175 (2024) - 2023
- [c7]Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Maximilian Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds:
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. MLHC 2023: 588-611 - [c6]Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes:
Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. NeurIPS 2023 - [c5]Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. NeurIPS 2023 - [c4]Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong, Brieuc Lehmann:
Quasi-Bayesian nonparametric density estimation via autoregressive predictive updates. UAI 2023: 658-668 - [e2]Javier Antorán, Arno Blaas, Kelly Buchanan, Fan Feng, Vincent Fortuin, Sahra Ghalebikesabi, Andreas Kriegler, Ian Mason, David Rohde, Francisco J. R. Ruiz, Tobias Uelwer, Yubin Xie, Rui Yang:
Proceedings on "I Can't Believe It's Not Better: Failure Modes in the Age of Foundation Models" at NeurIPS 2023 Workshops, 16 December 2023, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 239, PMLR 2023 [contents] - [i8]Sahra Ghalebikesabi, Leonard Berrada, Sven Gowal, Ira Ktena, Robert Stanforth, Jamie Hayes, Soham De, Samuel L. Smith, Olivia Wiles, Borja Balle:
Differentially Private Diffusion Models Generate Useful Synthetic Images. CoRR abs/2302.13861 (2023) - [i7]Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Max Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier González Hernández, Julia Greissl, Edward Meeds:
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. CoRR abs/2304.13737 (2023) - [i6]Veit David Wild, Sahra Ghalebikesabi, Dino Sejdinovic, Jeremias Knoblauch:
A Rigorous Link between Deep Ensembles and (Variational) Bayesian Methods. CoRR abs/2305.15027 (2023) - [i5]Jack Jewson, Sahra Ghalebikesabi, Chris C. Holmes:
Differentially Private Statistical Inference through β-Divergence One Posterior Sampling. CoRR abs/2307.05194 (2023) - 2022
- [c3]Sahra Ghalebikesabi, Harry Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Mitigating statistical bias within differentially private synthetic data. UAI 2022: 696-705 - [e1]Javier Antorán, Arno Blaas, Fan Feng, Sahra Ghalebikesabi, Ian Mason, Melanie F. Pradier, David Rohde, Francisco J. R. Ruiz, Aaron Schein:
Proceedings on "I Can't Believe It's Not Better! - Understanding Deep Learning Through Empirical Falsification" at NeurIPS 2022 Workshops, 03 December 2022, New Orleans, Louisiana, USA. Proceedings of Machine Learning Research 187, PMLR 2022 [contents] - [i4]Sahra Ghalebikesabi, Chris C. Holmes, Edwin Fong
, Brieuc Lehmann:
Density Estimation with Autoregressive Bayesian Predictives. CoRR abs/2206.06462 (2022) - 2021
- [c2]Sahra Ghalebikesabi, Rob Cornish, Chris C. Holmes, Luke J. Kelly:
Deep Generative Missingness Pattern-Set Mixture Models. AISTATS 2021: 3727-3735 - [c1]Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla DiazOrdaz, Chris C. Holmes:
On Locality of Local Explanation Models. NeurIPS 2021: 18395-18407 - [i3]Sahra Ghalebikesabi, Rob Cornish, Luke J. Kelly, Chris C. Holmes:
Deep Generative Pattern-Set Mixture Models for Nonignorable Missingness. CoRR abs/2103.03532 (2021) - [i2]Sahra Ghalebikesabi, Lucile Ter-Minassian, Karla Diaz-Ordaz, Chris C. Holmes:
On Locality of Local Explanation Models. CoRR abs/2106.14648 (2021) - [i1]Sahra Ghalebikesabi, Harrison Wilde, Jack Jewson, Arnaud Doucet, Sebastian J. Vollmer, Chris C. Holmes:
Bias Mitigated Learning from Differentially Private Synthetic Data: A Cautionary Tale. CoRR abs/2108.10934 (2021)
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last updated on 2024-07-20 21:24 CEST by the dblp team
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