Adji Bousso Dieng
Adji Bousso Dieng
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
2522016
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
1702016
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
992018
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
922017
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
762018
Topic modeling in embedding spaces
AB Dieng, FJR Ruiz, DM Blei
Transactions of the Association for Computational Linguistics 8, 439-453, 2020
652020
Prescribed generative adversarial networks
AB Dieng, FJR Ruiz, DM Blei, MK Titsias
arXiv preprint arXiv:1910.04302, 2019
252019
The dynamic embedded topic model
AB Dieng, FJR Ruiz, DM Blei
arXiv preprint arXiv:1907.05545, 2019
242019
Augment and Reduce: Stochastic Inference for Large Categorical Distributions
FJR Ruiz, MK Titsias, AB Dieng, DM Blei
International Conference on Machine Learning, 2018
232018
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
182018
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
112016
Reweighted Expectation Maximization
AB Dieng, J Paisley
arXiv preprint arXiv:1906.05850, 2019
102019
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
82016
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
62020
John Paisley and David M. Blei.‘The χ-Divergence for Approximate Inference’
AB Dieng, D Tran, R Ranganath
arXiv preprint.(), 2016
62016
The χ-Divergence for Approximate Inference
AB Dieng, D Tran, R Ranganath, J Paisley, DM Blei
Neural Information Processing Systems, 2017
52017
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
3
Learning with reflective likelihoods
AB Dieng, K Cho, DM Blei, Y LeCun
12018
Consistency Regularization for Variational Auto-Encoders
S Sinha, AB Dieng
arXiv preprint arXiv:2105.14859, 2021
2021
Probing optical anisotropy of van der Waals materials with nano-infrared spectroscopy
F Ruta, A Sternbach, A Dieng, A McLeod, D Basov
Bulletin of the American Physical Society, 2021
2021
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