The $χ$-Divergence for Approximate Inference. - Adji B. Dieng; Dustin Tran; Rajesh Ranganath; John W. Paisley; David M. Blei (CoRR, 2016)

Edward: A library for probabilistic modeling, inference, and criticism. - Dustin Tran; Alp Kucukelbir; Adji B. Dieng; Maja Rudolph; Dawen Liang; David M. Blei (CoRR, 2016)

TopicRNN: A Recurrent Neural Network with Long-Range Semantic Dependency. - Adji B. Dieng; Chong Wang 002; Jianfeng Gao 001; John W. Paisley (ICLR (Poster), 2017)

Variational Inference via chi Upper Bound Minimization. - Adji Bousso Dieng; Dustin Tran; Rajesh Ranganath; John W. Paisley; David M. Blei (NIPS, 2017)

Noisin: Unbiased Regularization for Recurrent Neural Networks. - Adji Bousso Dieng; Rajesh Ranganath; Jaan Altosaar; David M. Blei (ICML, 2018)

Augment and Reduce: Stochastic Inference for Large Categorical Distributions. - Francisco J. R. Ruiz; Michalis K. Titsias; Adji B. Dieng; David M. Blei (ICML, 2018)

Avoiding Latent Variable Collapse with Generative Skip Models. - Adji B. Dieng; Yoon Kim; Alexander M. Rush; David M. Blei (AISTATS, 2019)

Reweighted Expectation Maximization. - Adji B. Dieng; John W. Paisley (CoRR, 2019)

The Dynamic Embedded Topic Model. - Adji B. Dieng; Francisco J. R. Ruiz; David M. Blei (CoRR, 2019)

Prescribed Generative Adversarial Networks. - Adji B. Dieng; Francisco J. R. Ruiz; David M. Blei; Michalis K. Titsias (CoRR, 2019)

Topic Modeling in Embedding Spaces. - Adji Bousso Dieng; Francisco J. R. Ruiz; David M. Blei (Trans. Assoc. Comput. Linguistics, 2020)

Deep Probabilistic Graphical Modeling. - Adji Bousso Dieng (2020)

Consistency Regularization for Variational Auto-Encoders. - Samarth Sinha; Adji Bousso Dieng (NeurIPS, 2021)

Deep Probabilistic Graphical Modeling. - Adji B. Dieng (CoRR, 2021)

Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients. - Kyurae Kim; Jisu Oh; Jacob R. Gardner; Adji Bousso Dieng; Hongseok Kim (NeurIPS, 2022)

LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions. - Andre Niyongabo Rubungo; Craig Arnold; Barry P. Rand; Adji Bousso Dieng (CoRR, 2023)

DMLR: Data-centric Machine Learning Research - Past, Present and Future. - Luis Oala; Manil Maskey; Lilith Bat-Leah; Alicia Parrish; Nezihe Merve Gürel; Tzu-Sheng Kuo; Yang Liu 018; Rotem Dror; Danilo Brajovic; Xiaozhe Yao; Max Bartolo; William Gaviria Rojas; et al. (CoRR, 2023)

The Vendi Score: A Diversity Evaluation Metric for Machine Learning. - Dan Friedman; Adji Bousso Dieng (Trans. Mach. Learn. Res., 2023)

Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning. - Amey P. Pasarkar; Adji Bousso Dieng (AISTATS, 2024)

Constraint-Aware Diffusion Models for Trajectory Optimization. - Anjian Li; Zihan Ding; Adji Bousso Dieng; Ryne Beeson (DDDAS/Infosymbiotics, 2024)

Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design. - Quan Nguyen; Adji Bousso Dieng (ICML, 2024)

Beyond Aesthetics: Cultural Competence in Text-to-Image Models. - Nithish Kannen; Arif Ahmad; Marco Andreetto; Vinodkumar Prabhakaran; Utsav Prabhu; Adji Bousso Dieng; Pushpak Bhattacharyya; Shachi Dave (NeurIPS, 2024)

Efficient and Guaranteed-Safe Non-Convex Trajectory Optimization with Constrained Diffusion Model. - Anjian Li; Zihan Ding; Adji Bousso Dieng; Ryne Beeson (CoRR, 2024)

Relational Reasoning On Graphs Using Opinion Dynamics. - Yulong Yang 003; Bowen Feng; Keqin Wang; Naomi Ehrich Leonard; Adji Bousso Dieng; Christine Allen-Blanchette (CoRR, 2024)

LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction. - Andre Niyongabo Rubungo; Kangming Li; Jason Hattrick-Simpers; Adji Bousso Dieng (CoRR, 2024)

Behavior-Inspired Neural Networks for Relational Inference. - Yulong Yang 003; Bowen Feng; Keqin Wang; Naomi Ehrich Leonard; Adji Bousso Dieng; Christine Allen-Blanchette (AISTATS, 2025)

DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization. - Anjian Li; Zihan Ding; Adji Bousso Dieng; Ryne Beeson (L4DC, 2025)

Alternators For Sequence Modeling. - Mohammad Reza Rezaei; Adji Bousso Dieng (Trans. Mach. Learn. Res., 2025)

The α-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance. - Mohammad Reza Rezaei; Adji Bousso Dieng (CoRR, 2025)

The Vendiscope: An Algorithmic Microscope For Data Collections. - Amey P. Pasarkar; Adji Bousso Dieng (CoRR, 2025)

Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs. - Mohammad Reza Rezaei; Adji Bousso Dieng (CoRR, 2025)

Building Machine Learning Challenges for Anomaly Detection in Science. - Elizabeth G. Campolongo; Yuan-Tang Chou; Ekaterina Govorkova; Wahid Bhimji; Wei-Lun Chao; Chris Harris; Shih-Chieh Hsu; Hilmar Lapp; Mark S. Neubauer; Josephine M. Namayanja; Aneesh Subramanian; Philip C. Harris; et al. (CoRR, 2025)

Vendi Information Gain: An Alternative To Mutual Information For Science And Machine Learning. - Quan Nguyen; Adji Bousso Dieng (CoRR, 2025)

Alternators With Noise Models. - Mohammad Reza Rezaei; Adji Bousso Dieng (CoRR, 2025)