Adji Bousso Dieng
Senegalese computer scientist
Adji Bousso Dieng's AcademicInfluence.com Rankings
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Computer Science
Adji Bousso Dieng's Degrees
- PhD Computer Science Stanford University
- Masters Computer Science Stanford University
- Bachelors Computer Science Stanford University
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Why Is Adji Bousso Dieng Influential?
(Suggest an Edit or Addition)According to Wikipedia, Adji Bousso Dieng is a Senegalese Computer Scientist and Statistician working in the field of Artificial Intelligence. Her research bridges probabilistic graphical models and deep learning to discover meaningful structure from unlabelled data. She is currently an Artificial Intelligence Research Scientist at Google Brain in Mountain View, California. In 2021, she will start her tenure-track faculty position at Princeton University becoming the first Black female faculty member in the School of Engineering and Applied Science as well as the first Black faculty member ever in the Department of Computer Science. Dieng recently founded the non-profit “The Africa I Know” with the goal to inspire young Africans to pursue careers in STEM and AI by showcasing African role models, informing the general public about developments in STEM and AI by Africans, and educating the general public about the rich history of Africa.
Adji Bousso Dieng's Published Works
Published Works
- Edward: A library for probabilistic modeling, inference, and criticism (2016) (288)
- Topic Modeling in Embedding Spaces (2019) (264)
- TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency (2016) (209)
- Avoiding Latent Variable Collapse With Generative Skip Models (2018) (143)
- Variational Inference via χ Upper Bound Minimization (2017) (103)
- Readmission prediction via deep contextual embedding of clinical concepts (2018) (99)
- Variational Inference via \chi Upper Bound Minimization (2016) (74)
- Prescribed Generative Adversarial Networks (2019) (56)
- The Dynamic Embedded Topic Model (2019) (53)
- Consistency Regularization for Variational Auto-Encoders (2021) (31)
- Augment and Reduce: Stochastic Inference for Large Categorical Distributions (2018) (21)
- Noisin: Unbiased Regularization for Recurrent Neural Networks (2018) (18)
- Reweighted Expectation Maximization (2019) (14)
- Quantitative nano-infrared spectroscopy of anisotropic van der Waals materials. (2020) (10)
- The $χ$-Divergence for Approximate Inference (2016) (9)
- The Vendi Score: A Diversity Evaluation Metric for Machine Learning (2022) (3)
- Learning with Reflective Likelihoods (2018) (3)
- Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients (2022) (2)
- The $\chi$-Divergence for Approximate Inference (2016) (1)
- Noise-Based Regularizers for Recurrent Neural Networks (2018) (1)
- Deep Probabilistic Graphical Modeling (2021) (0)
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What Schools Are Affiliated With Adji Bousso Dieng?
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