Alexander Lin

According to our database, Alexander Lin authored at least 17 papers between 2010 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

A Deep Learning Approach for Placing Magnetic Resonance Spectroscopy Voxels in Brain Tumors.

Sangyoon Lee, Francesca Branzoli, Thanh Nguyen, Ovidiu C. Andronesi, Alexander Lin, Roberto Liserre, Gerd Melkus, Clark Chen, Malgorzata Marjanska, Patrick J. Bolan

Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2024, 2024

An Efficient Algorithm For Clustered Multi-Task Compressive Sensing.

Alexander Lin, Demba E. Ba

Proceedings of the IEEE International Conference on Acoustics, 2024

2023

Word-Level Explanations for Analyzing Bias in Text-to-Image Models.

Alexander Lin, Lucas Monteiro Paes, Sree Harsha Tanneru, Suraj Srinivas, Himabindu Lakkaraju

CoRR, 2023

Change Management in Physical Network Lifecycle Automation.

Mohammad Al-Fares, Virginia Beauregard, Kevin Grant, Angus Griffith, Jahangir Hasan, Chen Huang, Quan Leng, Jiayao Li, Alexander Lin, Zhuotao Liu, Ahmed Mansy, Bill Martinusen, Nikil Mehta, Jeffrey C. Mogul, Andrew Narver, Anshul Nigham, Melanie Obenberger, Sean Smith, Kurt Steinkraus, Sheng Sun, Edward Thiele, Amin Vahdat

Proceedings of the 2023 USENIX Annual Technical Conference, 2023

Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models.

Alexander Lin, Bahareh Tolooshams, Yves F. Atchadé, Demba E. Ba

Proceedings of the International Conference on Machine Learning, 2023

Investigating Scientific Misinformation Using Different Modes of Learning.

Autumn Toney-Wails, Kornraphop Kawintiranon, Lisa Singh, Paul-Emmanuel Courtines, Alexander Lin, Haofei Zhang

Proceedings of the Workshop on Scientific Document Understanding co-located with 37th AAAI Conference on Artificial Inteligence (AAAI 2023), 2023

2022

Covariance-Free Sparse Bayesian Learning.

Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba

IEEE Trans. Signal Process., 2022

Incorporating knowledge of plates in batch normalization improves generalization of deep learning for microscopy images.

Alexander Lin, Alex Lu

Proceedings of the Machine Learning in Computational Biology, 21-22 November 2022, Online, 2022

High-Dimensional Sparse Bayesian Learning without Covariance Matrices.

Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba

Proceedings of the IEEE International Conference on Acoustics, 2022

Mixture Model Auto-Encoders: Deep Clustering Through Dictionary Learning.

Alexander Lin, Andrew H. Song, Demba E. Ba

Proceedings of the IEEE International Conference on Acoustics, 2022

2021

Educational impact of an Augmented Reality (AR) application for teaching structural systems to non-engineering students.

Xinping Hu, Yang Miang Goh, Alexander Lin

Adv. Eng. Informatics, 2021

Action-Based Conversations Dataset: A Corpus for Building More In-Depth Task-Oriented Dialogue Systems.

Derek Chen, Howard Chen, Yi Yang, Alexander Lin, Zhou Yu

Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

2020

Autoregressive Knowledge Distillation through Imitation Learning.

Alexander Lin, Jeremy Wohlwend, Howard Chen, Tao Lei

Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing, 2020

2019

Universal Causal Evaluation Engine: An API for empirically evaluating causal inference models.

Alexander Lin, Amil Merchant, Suproteem K. Sarkar, Alexander D'Amour

Proceedings of the 2019 ACM SIGKDD Workshop on Causal Discovery, 2019

Clustering Time Series with Nonlinear Dynamics: A Bayesian Non-Parametric and Particle-Based Approach.

Alexander Lin, Yingzhuo Zhang, Jeremy Heng, Stephen A. Allsop, Kay M. Tye, Pierre E. Jacob, Demba E. Ba

Proceedings of the 22nd International Conference on Artificial Intelligence and Statistics, 2019

2011

Algorithms for characterizing brain metabolites in two-dimensional in vivo MR correlation spectroscopy.

Daniel Cocuzzo, Alexander Lin, Saadallah Ramadan, Carolyn Mountford, Nirmal Keshava

Proceedings of the 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2011

2010

Neuro magnetic resonance spectroscopy using wavelet decomposition and statistical testing identifies biochemical changes in people with spinal cord injury and pain.

Peter Stanwell, Philip Siddall, Nirmal Keshava, Daniel Cocuzzo, Saadallah Ramadan, Alexander Lin, David Herbert, Ashley Craig, Yvonne Tran, James W. Middleton, Shiva Gautam, Michael Cousins, Carolyn Mountford

NeuroImage, 2010