activity
20192026
most citedLearnable Bernoulli Dropout for Bayesian Deep Learning

20 citations · 35 across the 4 of their papers we have counts for

collaborators

5 papers

stat.ML2026

Certified by Abstention: Distribution-Free Guarantees for Chain-of-Thought Verifiers at Small Calibration Budgets

Arjun Balaji

Signals that predict whether a chain-of-thought (CoT) trace is correct are compared by AUC, but deploying one requires a threshold with a guarantee. We ask what distribution-free s…

cs.LG2022★ 2 cited

VFDS: Variational Foresight Dynamic Selection in Bayesian Neural Networks for Efficient Human Activity Recognition

Randy Ardywibowo, Shahin Boluki, Zhangyang Wang +3

In many machine learning tasks, input features with varying degrees of predictive capability are acquired at varying costs. In order to optimize the performance-cost trade-off, one…

cs.LG2020★ 10 cited

NADS: Neural Architecture Distribution Search for Uncertainty Awareness

Randy Ardywibowo, Shahin Boluki, Xinyu Gong +2

Machine learning (ML) systems often encounter Out-of-Distribution (OoD) errors when dealing with testing data coming from a distribution different from training data. It becomes im…

cs.LG2020★ 20 cited

Learnable Bernoulli Dropout for Bayesian Deep Learning

Shahin Boluki, Randy Ardywibowo, Siamak Zamani Dadaneh +2

In this work, we propose learnable Bernoulli dropout (LBD), a new model-agnostic dropout scheme that considers the dropout rates as parameters jointly optimized with other model pa…

cs.LG2019★ 3 cited

Adaptive Activity Monitoring with Uncertainty Quantification in Switching Gaussian Process Models

Randy Ardywibowo, Guang Zhao, Zhangyang Wang +3

Emerging wearable sensors have enabled the unprecedented ability to continuously monitor human activities for healthcare purposes. However, with so many ambient sensors collecting…