Dustin Tran
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
17
Venues
6
Active years
2016–2023
Best venue rank
A*
Where they publish
Papers
17 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2023 | ICML | Scaling Vision Transformers to 22 Billion Parameters. | Mostafa Dehghani, Josip Djolonga, Basil Mustafa, Piotr Padlewski, Jonathan Heek, Justin Gilmer, Andreas Peter Steiner, Mathilde Caron, Robert Geirhos, Ibrahim Alabdulmohsin, Rodolphe Jenatton, Lucas Beyer, Michael Tschannen, Anurag Arnab, Xiao Wang, Carlos Riquelme Ruiz, Matthias Minderer, Joan Puigcerver, Utku Evci, Manoj Kumar, Sjoerd van Steenkiste, Gamaleldin Fathy Elsayed, Aravindh Mahendran, Fisher Yu, Avital Oliver, Fantine Huot, Jasmijn Bastings, Mark Collier, Alexey A. Gritsenko, Vighnesh Birodkar, Cristina Nader Vasconcelos, Yi Tay, Thomas Mensink, Alexander Kolesnikov, Filip Pavetic, Dustin Tran, Thomas Kipf, Mario Lucic, Xiaohua Zhai, Daniel Keysers, Jeremiah J. Harmsen, Neil Houlsby |
| 2023 | ICML | A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models. | James Urquhart Allingham, Jie Ren, Michael W. Dusenberry, Xiuye Gu, Yin Cui, Dustin Tran, Jeremiah Zhe Liu, Balaji Lakshminarayanan |
| 2021 | ICLR | Training independent subnetworks for robust prediction. | Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran |
| 2021 | ICLR | Combining Ensembles and Data Augmentation Can Harm Your Calibration. | Yeming Wen, Ghassen Jerfel, Rafael Muller, Michael W. Dusenberry, Jasper Snoek, Balaji Lakshminarayanan, Dustin Tran |
| 2020 | ICLR | BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning. | Yeming Wen, Dustin Tran, Jimmy Ba |
| 2020 | ICML | Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors. | Michael Dusenberry, Ghassen Jerfel, Yeming Wen, Yi-An Ma, Jasper Snoek, Katherine A. Heller, Balaji Lakshminarayanan, Dustin Tran |
| 2020 | RecSys | Demonstrating Principled Uncertainty Modeling for Recommender Ecosystems with RecSim NG. | Martin Mladenov, Chih-Wei Hsu, Vihan Jain, Eugene Ie, Christopher Colby, Nicolas Mayoraz, Hubert Pham, Dustin Tran, Ivan Vendrov, Craig Boutilier |
| 2019 | CVPR | Measuring Calibration in Deep Learning. | Jeremy Nixon, Michael W. Dusenberry, Linchuan Zhang, Ghassen Jerfel, Dustin Tran |
| 2019 | ICLR | Discrete Flows: Invertible Generative Models of Discrete Data. | Dustin Tran, Keyon Vafa, Kumar Krishna Agrawal, Laurent Dinh, Ben Poole |
| 2019 | UAI | Noise Contrastive Priors for Functional Uncertainty. | Danijar Hafner, Dustin Tran, Timothy P. Lillicrap, Alex Irpan, James Davidson |
| 2018 | ICLR | Implicit Causal Models for Genome-wide Association Studies. | Dustin Tran, David M. Blei |
| 2018 | ICLR | Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches. | Yeming Wen, Paul Vicol, Jimmy Ba, Dustin Tran, Roger B. Grosse |
| 2018 | ICML | Image Transformer. | Niki Parmar, Ashish Vaswani, Jakob Uszkoreit, Lukasz Kaiser, Noam Shazeer, Alexander Ku, Dustin Tran |
| 2017 | ICLR | Deep Probabilistic Programming. | Dustin Tran, Matthew D. Hoffman, Rif A. Saurous, Eugene Brevdo, Kevin Murphy, David M. Blei |
| 2016 | AISTATS | Towards Stability and Optimality in Stochastic Gradient Descent. | Panos Toulis, Dustin Tran, Edoardo M. Airoldi |
| 2016 | AISTATS | Spectral M-estimation with Applications to Hidden Markov Models. | Dustin Tran, Minjae Kim, Finale Doshi-Velez |
| 2016 | ICML | Hierarchical Variational Models. | Rajesh Ranganath, Dustin Tran, David M. Blei |