Jalaian, Brian

6 publications

ECML-PKDD 2025 Towards Interpretable Adversarial Examples via Sparse Adversarial Attack Fudong Lin, Jiadong Lou, Hao Wang, Brian Jalaian, Xu Yuan

MLJ 2023 Decentralized Bayesian Learning with Metropolis-Adjusted Hamiltonian Monte Carlo Vyacheslav Kungurtsev, Adam D. Cobb, Tara Javidi, Brian Jalaian

MLJ 2023 Reducing Classifier Overconfidence Against Adversaries Through Graph Algorithms Leonardo Teixeira, Brian Jalaian, Bruno Ribeiro

UAI 2021 Scaling Hamiltonian Monte Carlo Inference for Bayesian Neural Networks with Symmetric Splitting Adam D. Cobb, Brian Jalaian

UAI 2020 Generalized Bayesian Posterior Expectation Distillation for Deep Neural Networks Meet Vadera, Brian Jalaian, Benjamin Marlin

NeurIPS 2019 Attribution-Based Confidence Metric for Deep Neural Networks Susmit Jha, Sunny Raj, Steven Fernandes, Sumit K Jha, Somesh Jha, Brian Jalaian, Gunjan Verma, Ananthram Swami