Adji Bousso Dieng
Adji Bousso Dieng
Columbia University
Verified email at columbia.edu - Homepage
Title
Cited by
Cited by
Year
Edward: A library for probabilistic modeling, inference, and criticism
D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei
arXiv preprint arXiv:1610.09787, 2016
2302016
Topicrnn: A recurrent neural network with long-range semantic dependency
AB Dieng, C Wang, J Gao, J Paisley
International Conference on Learning Representations (ICLR 2017), 2016
1562016
Avoiding Latent Variable Collapse with Generative Skip Models
AB Dieng, Y Kim, AM Rush, D Blei
Proceedings of the 22 International Conference on Artificial Intelligence …, 2018
862018
Variational Inference via Upper Bound Minimization
AB Dieng, D Tran, R Ranganath, J Paisley, D Blei
Advances in Neural Information Processing Systems, 2732-2741, 2017
812017
Readmission prediction via deep contextual embedding of clinical concepts
C Xiao, T Ma, AB Dieng, DM Blei, F Wang
PloS one 13 (4), e0195024, 2018
592018
Topic modeling in embedding spaces
AB Dieng, FJR Ruiz, DM Blei
Transactions of the Association for Computational Linguistics 8, 439-453, 2020
412020
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
FJR Ruiz, MK Titsias, AB Dieng, DM Blei
International Conference on Machine Learning, 2018
202018
Prescribed generative adversarial networks
AB Dieng, FJR Ruiz, DM Blei, MK Titsias
arXiv preprint arXiv:1910.04302, 2019
172019
The dynamic embedded topic model
AB Dieng, FJR Ruiz, DM Blei
arXiv preprint arXiv:1907.05545, 2019
172019
Noisin: Unbiased Regularization for Recurrent Neural Networks
AB Dieng, R Ranganath, J Altosaar, DM Blei
Proceedings of the 35th International Conference on Machine Learning (ICML …, 2018
142018
Edward: A library for probabilistic modeling, inference, and criticism, 2016
D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei
arXiv preprint arXiv:1610.09787, 2016
122016
The χ-Divergence for Approximate Inference
AB Dieng, D Tran, R Ranganath, J Paisley, DM Blei
Neural Information Processing Systems, 2017
52017
Edward: A library for probabilistic modeling, inference, and criticism. arXiv (2016)
D Tran, A Kucukelbir, AB Dieng, M Rudolph, D Liang, DM Blei
arXiv preprint arXiv:1610.09787, 2016
52016
John Paisley and David M. Blei.‘The χ-Divergence for Approximate Inference’
AB Dieng, D Tran, R Ranganath
arXiv preprint.(), 2016
52016
Reweighted Expectation Maximization
AB Dieng, J Paisley
arXiv preprint arXiv:1906.05850, 2019
42019
John Paisley, and David Blei. 2017. Variational Inference via\chi Upper Bound Minimization
AB Dieng, D Tran, R Ranganath
Advances in Neural Information Processing Systems, 2732-2741, 0
4
Quantitative Nanoinfrared Spectroscopy of Anisotropic van der Waals Materials
FL Ruta, AJ Sternbach, AB Dieng, AS McLeod, DN Basov
Nano Letters 20 (11), 7933-7940, 2020
22020
Learning with Reflective Likelihoods
AB Dieng, K Cho, DM Blei, Y LeCun
12018
Deep Probabilistic Graphical Modeling
AB Dieng
Columbia University, 2020
2020
The African Master's in Machine Intelligence and the potential of AI in Africa
AB Dieng
2019 Annual Meeting, 2019
2019
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Articles 1–20