Sotabase

Career

· Assistant Professor, Princeton University2021–
· Research Scientist, Google DeepMind2020–2025
· Ph.D. in Statistics, Columbia University2014–2020
· Junior Professional Associate, The World Bank2013–2014
· Master in Applied Statistics, Cornell University2012–2013
· Diplome d'Ingenieur, Télécòom ParisTech2009–2013
· Preparatory Classes for Grandes Écoles, Lycée Henri-IV2007–2009

Publications (67)

Topic Modeling in Embedding Spaces
Transactions of the Association for Computational Linguistics · 2019
772
cited
Edward: A library for probabilistic modeling, inference, and criticism
arXiv.org · 2016
303
cited
TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
International Conference on Learning Representations · 2016
249
cited
The Vendi Score: A Diversity Evaluation Metric for Machine Learning
Trans. Mach. Learn. Res. · 2022
206
cited
Avoiding Latent Variable Collapse With Generative Skip Models
International Conference on Artificial Intelligence and Statistics · 2018
184
cited
Variational Inference via χ Upper Bound Minimization
2017
133
cited
Readmission prediction via deep contextual embedding of clinical concepts
PLoS ONE · 2018
112
cited
The Dynamic Embedded Topic Model
arXiv.org · 2019
103
cited
Consistency Regularization for Variational Auto-Encoders
Neural Information Processing Systems · 2021
76
cited
Prescribed Generative Adversarial Networks
arXiv.org · 2019
61
cited
The $\chi$-Divergence for Approximate Inference
2016
35
cited
Property-guided generation of complex polymer topologies using variational autoencoders
npj Computational Materials · 2024
33
cited
Beyond Aesthetics: Cultural Competence in Text-to-Image Models
Neural Information Processing Systems · 2024
32
cited
Noisin: Unbiased Regularization for Recurrent Neural Networks
International Conference on Machine Learning · 2018
25
cited
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning
International Conference on Artificial Intelligence and Statistics · 2023
23
cited
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
International Conference on Machine Learning · 2018
22
cited
Diversity-driven, efficient exploration of a MOF design space to optimize MOF properties
Chemical Science · 2024
17
cited
DMLR: Data-centric Machine Learning Research - Past, Present and Future
arXiv.org · 2023
17
cited
Reweighted Expectation Maximization
arXiv.org · 2019
17
cited
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design
International Conference on Machine Learning · 2024
14
cited
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