Dustin Tran
31 papers · 2015–2024 · 7 venues · across top CS/AI venues
This profile combines several different researchers. Authors are keyed by name, and this name's papers fall into 11 separate collaboration groups - the largest holds only 39% of them. Pick the group below that matches the researcher you mean. How a shared name is split.
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Which Dustin Tran?
4 groups of papers that share co-authors internally but none with each other - each most likely a different researcher. Pick one to see its papers.
with Balaji Lakshminarayanan, Yeming Wen, Jasper Snoek
12 papers
· 2018–2023
· ICLR, NeurIPS, ICML
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A Simple Approach to Improve Single-Model Deep Uncertainty via Distance-Awareness
JMLR 2023
A Simple Zero-shot Prompt Weighting Technique to Improve Prompt Ensembling in Text-Image Models
ICML 2023
Scaling Vision Transformers to 22 Billion Parameters
ICML 2023
Combining Ensembles and Data Augmentation Can Harm Your Calibration
ICLR 2021
Revisiting the Calibration of Modern Neural Networks
NeurIPS 2021
Soft Calibration Objectives for Neural Networks
NeurIPS 2021
Training independent subnetworks for robust prediction
ICLR 2021
BatchEnsemble: an Alternative Approach to Efficient Ensemble and Lifelong Learning
ICLR 2020
Efficient and Scalable Bayesian Neural Nets with Rank-1 Factors
ICML 2020
Hyperparameter Ensembles for Robustness and Uncertainty Quantification
NeurIPS 2020
Simple and Principled Uncertainty Estimation with Deterministic Deep Learning via Distance Awareness
NeurIPS 2020
Flipout: Efficient Pseudo-Independent Weight Perturbations on Mini-Batches
ICLR 2018
7 papers whose co-authors appear nowhere else under this name
Long-form factuality in large language models
NeurIPS 2024
On the Discrepancy between Density Estimation and Sequence Generation
EMNLP 2020
Discrete Flows: Invertible Generative Models of Discrete Data
NeurIPS 2019
Autoconj: Recognizing and Exploiting Conjugacy Without a Domain-Specific Language
NeurIPS 2018
Simple, Distributed, and Accelerated Probabilistic Programming
NeurIPS 2018
Spectral M-estimation with Applications to Hidden Markov Models
AISTATS 2016
Towards Stability and Optimality in Stochastic Gradient Descent
AISTATS 2016