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Melanie F. Pradier
Melanie F. Pradier
Microsoft Research
Zweryfikowany adres z microsoft.com - Strona główna
Tytuł
Cytowane przez
Cytowane przez
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How machine-learning recommendations influence clinician treatment selections: the example of antidepressant selection
M Jacobs, MF Pradier, TH McCoy Jr, RH Perlis, F Doshi-Velez, KZ Gajos
Translational psychiatry 11 (1), 108, 2021
772021
Designing AI for trust and collaboration in time-constrained medical decisions: A sociotechnical lens
M Jacobs, J He, M F. Pradier, B Lam, AC Ahn, TH McCoy, RH Perlis, ...
Proceedings of the 2021 chi conference on human factors in computing systems …, 2021
502021
Economic complexity unfolded: Interpretable model for the productive structure of economies
Z Utkovski, MF Pradier, V Stojkoski, F Perez-Cruz, L Kocarev
PloS one 13 (8), e0200822, 2018
332018
Predicting treatment dropout after antidepressant initiation
MF Pradier, TH McCoy Jr, M Hughes, RH Perlis, F Doshi-Velez
Translational psychiatry 10 (1), 60, 2020
182020
Output-constrained Bayesian neural networks
W Yang, L Lorch, MA Graule, S Srinivasan, A Suresh, J Yao, MF Pradier, ...
arXiv preprint arXiv:1905.06287, 2019
182019
Emotion recognition from speech signals and perception of music
MF Pradier
Universität Stuttgart Institut für Systemtheorie und Bildschirmtechnik …, 2011
132011
Preferential mixture-of-experts: Interpretable models that rely on human expertise as much as possible
MF Pradier, J Zazo, S Parbhoo, RH Perlis, M Zazzi, F Doshi-Velez
AMIA Summits on Translational Science Proceedings 2021, 525, 2021
112021
General latent feature models for heterogeneous datasets
I Valera, MF Pradier, M Lomeli, Z Ghahramani
arXiv preprint arXiv:1706.03779, 2017
112017
General latent feature models for heterogeneous datasets
I Valera, MF Pradier, M Lomeli, Z Ghahramani
The Journal of Machine Learning Research 21 (1), 4027-4075, 2020
102020
Latent projection bnns: Avoiding weight-space pathologies by learning latent representations of neural network weights
MF Pradier, W Pan, J Yao, S Ghosh, F Doshi-Velez
Workshop on Bayesian Deep Learning, NIPS, 2018
102018
Prior design for dependent Dirichlet processes: An application to marathon modeling
M F. Pradier, F JR Ruiz, F Perez-Cruz
PloS one 11 (1), e0147402, 2016
102016
General latent feature modeling for data exploration tasks
I Valera, MF Pradier, Z Ghahramani
arXiv preprint arXiv:1707.08352, 2017
82017
Assessment of a prediction model for antidepressant treatment stability using supervised topic models
MC Hughes, MF Pradier, AS Ross, TH McCoy, RH Perlis, F Doshi-Velez
JAMA Network Open 3 (5), e205308-e205308, 2020
62020
Projected BNNs: Avoiding weight-space pathologies by learning latent representations of neural network weights
MF Pradier, W Pan, J Yao, S Ghosh, F Doshi-Velez
arXiv preprint arXiv:1811.07006, 2018
62018
Predicting change in diagnosis from major depression to bipolar disorder after antidepressant initiation
MF Pradier, MC Hughes, TH McCoy Jr, SA Barroilhet, F Doshi-Velez, ...
Neuropsychopharmacology 46 (2), 455-461, 2021
52021
Sparse three-parameter restricted indian buffet process for understanding international trade
MF Pradier, V Stojkoski, Z Utkovski, L Kocorev, F Perez-Cruz
2018 IEEE International Conference on Acoustics, Speech and Signal …, 2018
52018
Evaluating approximate inference in Bayesian deep learning
AG Wilson, P Izmailov, MD Hoffman, Y Gal, Y Li, MF Pradier, S Vikram, ...
NeurIPS 2021 Competitions and Demonstrations Track, 113-124, 2022
42022
Towards expressive priors for Bayesian neural networks: Poisson process radial basis function networks
B Coker, MF Pradier, F Doshi-Velez
arXiv preprint arXiv:1912.05779, 2019
42019
Case-control Indian buffet process identifies biomarkers of response to Codrituzumab
MF Pradier, B Reis, L Jukofsky, F Milletti, T Ohtomo, F Perez-Cruz, O Puig
BMC cancer 19, 1-7, 2019
42019
Challenges in computing and optimizing upper bounds of marginal likelihood based on chi-square divergences
MF Pradier, MC Hughes, F Doshi-Velez
Second Symposium on Advances in Approximate Bayesian Inference, 2019
42019
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