Adji Bousso Dieng

38 papers A* 5A 2Journal 26Unranked 3
YearRankTypeTitle / Venue / Authors
2026 J jnl
Vendi Novelty Scores for Out-of-Distribution Detection.
CoRR
Amey P. Pasarkar, Adji Bousso Dieng
2025 J jnl
Alternators For Sequence Modeling.
Trans. Mach. Learn. Res.
Mohammad Reza Rezaei, Adji Bousso Dieng
2025 J jnl
Alternators With Noise Models.
CoRR
Mohammad Reza Rezaei, Adji Bousso Dieng
2025 J jnl
Are neural scaling laws leading quantum chemistry astray?
CoRR
Siwoo Lee, Adji Bousso Dieng
2025 A conf
Behavior-Inspired Neural Networks for Relational Inference.
AISTATS
Yulong Yang, Bowen Feng, Keqin Wang, Naomi Ehrich Leonard, Adji Bousso Dieng, Christine Allen-Blanchette
2025 J jnl
Building Machine Learning Challenges for Anomaly Detection in Science.
CoRR
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, Advaith Anand, David Edward Carlyn, Subhankar Ghosh, Christopher G. Lawrence, Eric A. Moreno, Ryan Raikman, Jiaman Wu, Ziheng Zhang, Bayu Adhi, Mohammad Ahmadi Gharehtoragh, Saúl Alonso-Monsalve, Marta Babicz, Furqan Baig, Namrata Banerji, William Bardon, Tyler Barna, Tanya Y. Berger-Wolf, Adji Bousso Dieng, Micah Brachman, Quentin Buat, David C. Y. Hui, Phuong Cao, Franco Cerino, Yi-Chun Chang, Shivaji Chaulagain, An-Kai Chen, Deming Chen, Eric Chen, Chia-Jui Chou, Zih-Chen Ciou, Miles Cochran-Branson, Artur Cordeiro Oudot Choi, Michael Coughlin, Matteo Cremonesi, Maria Dadarlat, Peter Darch, Malina Desai, Daniel Diaz, Steven Dillmann, Javier M. Duarte, Isla Duporge, Urbas Ekka, Saba Entezari Heravi, Hao Fang, Rian Flynn, Geoffrey Fox, Emily Freed, Hang Gao, Jing Gao, Julia Gonski, Matthew J. Graham, Abolfazl Hashemi, Scott Hauck, James Hazelden, Joshua Henry Peterson, Duc Hoang, Wei Hu, Mirco Hünnefeld, David Hyde, Vandana P. Janeja, Nattapon Jaroenchai, Haoyi Jia, Yunfan Kang, Maksim Kholiavchenko, Elham E Khoda, Sangin Kim, Aditya Kumar, Bo-Cheng Lai, Trung Le, Chi-Wei Lee, Janghyeon Lee, Shaocheng Lee, Suzan van der Lee, Charles Lewis, Haitong Li, Haoyang Li, Henry Liao, Mia Liu, Xiaolin Liu, Xiulong Liu, Vladimir Loncar, Fangzheng Lyu, Ilya Makarov, Abhishikth Mallampalli Chen-Yu Mao, Alexander Michels, Alexander Migala, Farouk Mokhtar, Mathieu Morlighem
2025 — conf
DiffuSolve: Diffusion-based Solver for Non-convex Trajectory Optimization.
L4DC
Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson
2025 J jnl
LLM4Mat-bench: benchmarking large language models for materials property prediction.
Mach. Learn. Sci. Technol.
Andre Niyongabo Rubungo, Kangming Li, Jason Hattrick-Simpers, Adji Bousso Dieng
2025 J jnl
The Vendiscope: An Algorithmic Microscope For Data Collections.
CoRR
Amey P. Pasarkar, Adji Bousso Dieng
2025 J jnl
The α-Alternator: Dynamic Adaptation To Varying Noise Levels In Sequences Using The Vendi Score For Improved Robustness and Performance.
CoRR
Mohammad Reza Rezaei, Adji Bousso Dieng
2025 J jnl
Vendi Information Gain for Active Learning and its Application to Ecology.
CoRR
Quan Nguyen, Adji Bousso Dieng
2025 J jnl
Vendi Information Gain: An Alternative To Mutual Information For Science And Machine Learning.
CoRR
Quan Nguyen, Adji Bousso Dieng
2025 J jnl
Vendi-RAG: Adaptively Trading-Off Diversity And Quality Significantly Improves Retrieval Augmented Generation With LLMs.
CoRR
Mohammad Reza Rezaei, Adji Bousso Dieng
2024 J jnl
Alternators For Sequence Modeling.
CoRR
Mohammad Reza Rezaei, Adji Bousso Dieng
2024 A* conf
Beyond Aesthetics: Cultural Competence in Text-to-Image Models.
NeurIPS
Nithish Kannen, Arif Ahmad, Marco Andreetto, Vinodkumar Prabhakaran, Utsav Prabhu, Adji Bousso Dieng, Pushpak Bhattacharyya, Shachi Dave
2024 J jnl
Beyond Aesthetics: Cultural Competence in Text-to-Image Models.
CoRR
Nithish Kannen, Arif Ahmad, Marco Andreetto, Vinodkumar Prabhakaran, Utsav Prabhu, Adji Bousso Dieng, Pushpak Bhattacharyya, Shachi Dave
2024 — conf
Constraint-Aware Diffusion Models for Trajectory Optimization.
DDDAS/Infosymbiotics
Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson
2024 J jnl
Constraint-Aware Diffusion Models for Trajectory Optimization.
CoRR
Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson
2024 A conf
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning.
AISTATS
Amey P. Pasarkar, Adji Bousso Dieng
2024 J jnl
DMLR: Data-centric Machine Learning Research - Past, Present and Future.
J. Data-centric Mach. Learn. Res.
Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2024 J jnl
Efficient and Guaranteed-Safe Non-Convex Trajectory Optimization with Constrained Diffusion Model.
CoRR
Anjian Li, Zihan Ding, Adji Bousso Dieng, Ryne Beeson
2024 J jnl
LLM4Mat-Bench: Benchmarking Large Language Models for Materials Property Prediction.
CoRR
Andre Niyongabo Rubungo, Kangming Li, Jason Hattrick-Simpers, Adji Bousso Dieng
2024 A* conf
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design.
ICML
Quan Nguyen, Adji Bousso Dieng
2024 J jnl
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design.
CoRR
Quan Nguyen, Adji Bousso Dieng
2024 J jnl
Relational Reasoning On Graphs Using Opinion Dynamics.
CoRR
Yulong Yang, Bowen Feng, Keqin Wang, Naomi Ehrich Leonard, Adji Bousso Dieng, Christine Allen-Blanchette
2023 J jnl
Cousins Of The Vendi Score: A Family Of Similarity-Based Diversity Metrics For Science And Machine Learning.
CoRR
Amey P. Pasarkar, Adji Bousso Dieng
2023 J jnl
DMLR: Data-centric Machine Learning Research - Past, Present and Future.
CoRR
Luis Oala, Manil Maskey, Lilith Bat-Leah, Alicia Parrish, Nezihe Merve Gürel, Tzu-Sheng Kuo, Yang Liu, Rotem Dror, Danilo Brajovic, Xiaozhe Yao, Max Bartolo, William Gaviria Rojas, Ryan Hileman, Rainier Aliment, Michael W. Mahoney, Meg Risdal, Matthew Lease, Wojciech Samek, Debojyoti Dutta, Curtis G. Northcutt, Cody Coleman, Braden Hancock, Bernard Koch, Girmaw Abebe Tadesse, Bojan Karlas, Ahmed M. Alaa, Adji Bousso Dieng, Natasha F. Noy, Vijay Janapa Reddi, James Zou, Praveen K. Paritosh, Mihaela van der Schaar, Kurt Bollacker, Lora Aroyo, Ce Zhang, Joaquin Vanschoren, Isabelle Guyon, Peter Mattson
2023 J jnl
LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions.
CoRR
Andre Niyongabo Rubungo, Craig Arnold, Barry P. Rand, Adji Bousso Dieng
2023 J jnl
The Vendi Score: A Diversity Evaluation Metric for Machine Learning.
Trans. Mach. Learn. Res.
Dan Friedman, Adji Bousso Dieng
2022 A* conf
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients.
NeurIPS
Kyurae Kim, Jisu Oh, Jacob R. Gardner, Adji Bousso Dieng, Hongseok Kim
2022 J jnl
Markov Chain Score Ascent: A Unifying Framework of Variational Inference with Markovian Gradients.
CoRR
Kyurae Kim, Jisu Oh, Jacob R. Gardner, Adji Bousso Dieng, Hongseok Kim
2022 J jnl
The Vendi Score: A Diversity Evaluation Metric for Machine Learning.
CoRR
Dan Friedman, Adji Bousso Dieng
2021 A* conf
Consistency Regularization for Variational Auto-Encoders.
NeurIPS
Samarth Sinha, Adji Bousso Dieng
2020 — —
Deep Probabilistic Graphical Modeling.
Adji Bousso Dieng
2020 — ed.
Symposium on Advances in Approximate Bayesian Inference, AABI 2019, Vancouver, BC, Canada, December 8, 2019.
AABI
Cheng Zhang, Francisco J. R. Ruiz, Thang D. Bui, Adji Bousso Dieng, Dawen Liang
2020 J jnl
Topic Modeling in Embedding Spaces.
Trans. Assoc. Comput. Linguistics
Adji Bousso Dieng, Francisco J. R. Ruiz, David M. Blei
2018 A* conf
Noisin: Unbiased Regularization for Recurrent Neural Networks.
ICML
Adji Bousso Dieng, Rajesh Ranganath, Jaan Altosaar, David M. Blei
2017 — conf
Variational Inference via \chi Upper Bound Minimization.
NIPS
Adji Bousso Dieng, Dustin Tran, Rajesh Ranganath, John W. Paisley, David M. Blei