Melanie F. Pradier

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 16

Top Topics

Back Propagation

Generative Model

Poisson Process

Top Venues

J. Mach. Learn. Res.

Publications

Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa, Sahra Ghalebikesabi, Max Ilse, Steven Woodhouse, Rebecca Elyanow, Javier Zazo, Javier Gonzalez, Julia Greissl, Edward Meeds
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires. CoRR (2023)
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)
Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li
Repairing Neural Networks by Leaving the Right Past Behind. CoRR (2022)
Ryutaro Tanno, Melanie F. Pradier, Aditya V. Nori, Yingzhen Li
Repairing Neural Networks by Leaving the Right Past Behind. NeurIPS (2022)
Maia Jacobs, Jeffrey He, Melanie F. Pradier, Barbara 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)
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 (2021)
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)
Maia Jacobs, Jeffrey He, Melanie F. Pradier, Barbara 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 (2021)
Isabel Valera, Melanie F. Pradier, Maria Lomeli, Zoubin Ghahramani
General Latent Feature Models for Heterogeneous Datasets. J. Mach. Learn. Res. 21 (2020)
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 (2019)
Beau Coker, Melanie F. Pradier, Finale Doshi-Velez
Towards Expressive Priors for Bayesian Neural Networks: Poisson Process Radial Basis Function Networks. CoRR (2019)
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 (2018)
Melanie F. Pradier, Viktor Stojkoski, Zoran Utkovski, Ljupco Kocarev, Fernando Pérez-Cruz
Sparse Three-parameter Restricted Indian Buffet Process for Understanding International Trade. CoRR (2018)
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)
Isabel Valera, Melanie F. Pradier, Zoubin Ghahramani
General Latent Feature Modeling for Data Exploration Tasks. CoRR (2017)
Melanie F. Pradier, Pablo M. Olmos, Fernando Pérez-Cruz
Entropy-Constrained Scalar Quantization with a Lossy-Compressed Bit. Entropy 18 (12) (2016)