Publications
2024
Property-Guided Generation of Complex Polymer Topologies Using Variational Autoencoders
Shengli Jiang, Adji Bousso Dieng*, Michael Webb*
Read the paperEfficient and Guaranteed-Safe Non-Convex Trajectory Optimization with Constrained Diffusion Model
Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson
Read the paper2023
Vendi sampling for molecular simulations: Diversity as a force for faster convergence and better exploration
Amey P. Pasarkar, Gianluca M. Bencomo, Simon Olsson, Adji Bousso Dieng
Read the paperCousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning
Amey P. Pasarkar, Adji Bousso Dieng
Read the paperLLM-Prop: Predicting physical and electronic properties of crystalline solids from their text descriptions
Andre Niyongabo Rubungo, Craig Arnold, Barry P. Rand, Adji Bousso Dieng
Read the paper2022
The Vendi Score: A Diversity Evaluation Metric for Machine Learning
Dan Friedman, Adji Bousso Dieng
Read the paperMarkov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients
Kyurae Kim, Jisu Oh, Jacob R. Gardner, Adji Bousso Dieng, Hongseok Kim
Read the paperConsistency Regularization for Variational Auto-Encoders
Samarth Sinha, Adji Bousso Dieng
Read the paper2020
2019
The Dynamic Embedded Topic Model
Adji Bousso Dieng*, Francisco R. J. Ruiz*, David M. Blei
Read the paperPrescribed Generative Adversarial Networks
Adji Bousso Dieng, Francisco J. R. Ruiz, David M. Blei, Michalis K. Titsias
Read the paperTopic Modeling in Embedding Spaces
Adji Bousso Dieng, Francisco J. R. Ruiz, David M. Blei
Read the paperAvoiding Latent Variable Collapse With Generative Skip Models
Adji Bousso Dieng, Yoon Kim, Alexander M. Rush, David M. Blei
Read the paper2018
Quantitative Nanoinfrared Spectroscopy of Anisotropic van der Waals Materials
Francesco L. Ruta*, Aaron J. Sternbach, Adji Bousso Dieng, Alexander S. McLeod, and D. N. Basov
Read the paperNoisin: Unbiased Regularization for Recurrent Neural Networks
Adji Bousso Dieng, Rajesh Ranganath, Jaan Altosaar, David M. Blei
Read the paperAugment and Reduce: Stochastic Inference for Large Categorical Distributions
Francisco J. R. Ruiz, Michalis K. Titsias, Adji Bousso Dieng, David M. Blei
Read the paperReadmission prediction via deep contextual embedding of clinical concepts
Cao Xiao, Tengfei Ma, Adji Bousso Dieng, David M. Blei, Fei Wang
Read the paper2017
Variational Inference via χ-Upper Bound Minimization
Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John Paisley, David M. Blei
Read the paperTopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency
Adji Bousso Dieng, Chong Wang, Jianfeng Gao, John Paisley
Read the paperEdward: A library for probabilistic modeling, inference, and criticism
Dustin Tran, Alp Kucukelbir, Adji Bousso Dieng, Maja Rudolph, Dawen Liang, David M. Blei
Read the paper