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ORCIDMelanie F. Pradier
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- affiliation: Microsoft Health Futures, Cambridge, UK
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2020 – today
- 2024
[i11]Melanie F. Pradier, Javier González:
Beyond Flatland: A Geometric Take on Matching Methods for Treatment Effect Estimation. CoRR abs/2409.05459 (2024)- 2023
- [c6]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 - [i10]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) - 2022
- [c5]Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li:
Repairing Neural Networks by Leaving the Right Past Behind. NeurIPS 2022 - [e3]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] - [i9]Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li:
Repairing Neural Networks by Leaving the Right Past Behind. CoRR abs/2207.04806 (2022) - 2021
- [c4]Maia L. Jacobs, Jeffrey He, Melanie F. Pradier, Barbara D. Lam, Andrew C. Ahn, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Krzysztof Z. Gajos:
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CHI 2021: 659:1-659:14 - [c3]Andrew Gordon Wilson, Pavel Izmailov, Matthew D. Hoffman, Yarin Gal, Yingzhen Li, Melanie F. Pradier, Sharad Vikram, Andrew Y. K. Foong, Sanae Lotfi, Sebastian Farquhar:
Evaluating Approximate Inference in Bayesian Deep Learning. NeurIPS (Competition and Demos) 2021: 113-124 - [e2]Melanie F. Pradier, Aaron Schein, Stephanie L. Hyland, Francisco J. R. Ruiz, Jessica Zosa Forde:
I (Still) Can't Believe It's Not Better! Workshop at NeurIPS 2021, Virtual Workshop, December 13, 2021. Proceedings of Machine Learning Research 163, PMLR 2021 [contents] - [i8]Melanie F. Pradier, Javier Zazo, Sonali Parbhoo, Roy H. Perlis, Maurizio Zazzi, Finale Doshi-Velez:
Preferential Mixture-of-Experts: Interpretable Models that Rely on Human Expertise as much as Possible. CoRR abs/2101.05360 (2021) - [i7]Maia L. Jacobs, Jeffrey He, Melanie F. Pradier, Barbara D. Lam, Andrew C. Ahn, Thomas H. McCoy, Roy H. Perlis, Finale Doshi-Velez, Krzysztof Z. Gajos:
Designing AI for Trust and Collaboration in Time-Constrained Medical Decisions: A Sociotechnical Lens. CoRR abs/2102.00593 (2021) - 2020
- [j2]Isabel Valera
, Melanie F. Pradier, Maria Lomeli, Zoubin Ghahramani:
General Latent Feature Models for Heterogeneous Datasets. J. Mach. Learn. Res. 21: 100:1-100:49 (2020) - [c2]Beau Coker, Melanie Fernandes Pradier, Finale Doshi-Velez:
PoRB-Nets: Poisson Process Radial Basis Function Networks. UAI 2020: 1338-1347 - [e1]Jessica Zosa Forde, Francisco J. R. Ruiz, Melanie F. Pradier, Aaron Schein:
"I Can't Believe It's Not Better!" at NeurIPS Workshops, Virtual, December 12, 2020. Proceedings of Machine Learning Research 137, PMLR 2020 [contents]
2010 – 2019
- 2019
- [i6]Stefan G. Stark, Stephanie L. Hyland, Melanie Fernandes Pradier, Kjong-Van Lehmann, Andreas Wicki, Fernando Pérez-Cruz, Julia E. Vogt, Gunnar Rätsch:
Unsupervised Extraction of Phenotypes from Cancer Clinical Notes for Association Studies. CoRR abs/1904.12973 (2019) - [i5]Wanqian Yang, Lars Lorch, Moritz A. Graule, Srivatsan Srinivasan, Anirudh Suresh, Jiayu Yao, Melanie F. Pradier, Finale Doshi-Velez:
Output-Constrained Bayesian Neural Networks. CoRR abs/1905.06287 (2019) - [i4]Beau Coker, Melanie F. Pradier, Finale Doshi-Velez:
Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks. CoRR abs/1912.05779 (2019) - 2018
- [c1]Melanie F. Pradier, Viktor Stojkoski, Zoran Utkovski, Lujupco Kocorev, Fernando Pérez-Cruz:
Sparse Three-Parameter Restricted Indian Buffet Process for Understanding International Trade. ICASSP 2018: 2476-2480 - [i3]Melanie F. Pradier, Viktor Stojkoski, Zoran Utkovski, Ljupco Kocarev, Fernando Pérez-Cruz:
Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade. CoRR abs/1806.11518 (2018) - [i2]Melanie F. Pradier, Weiwei Pan, Jiayu Yao, Soumya Ghosh, Finale Doshi-Velez:
Latent Projection BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights. CoRR abs/1811.07006 (2018) - 2017
- [i1]Isabel Valera, Melanie F. Pradier, Zoubin Ghahramani:
General Latent Feature Modeling for Data Exploration Tasks. CoRR abs/1707.08352 (2017) - 2016
- [j1]Melanie F. Pradier, Pablo M. Olmos, Fernando Pérez-Cruz:
Entropy-Constrained Scalar Quantization with a Lossy-Compressed Bit. Entropy 18(12): 449 (2016)
Coauthor Index
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