Andrew H. Song

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 30

Top Topics

Dictionary Learning

Spectral Estimation

Covariance Matrices

Top Venues

IEEE Signal Process. Lett.

IEEE Trans. Signal Process.

Publications

Andrew H. Song, Richard J. Chen, Tong Ding, Drew F. K. Williamson, Guillaume Jaume, Faisal Mahmood
Morphological Prototyping for Unsupervised Slide Representation Learning in Computational Pathology. CoRR (2024)
Guillaume Jaume, Paul Doucet, Andrew H. Song, Ming Y. Lu, Cristina Almagro-Pérez, Sophia J. Wagner, Anurag J. Vaidya, Richard J. Chen, Drew F. K. Williamson, Ahrong Kim, Faisal Mahmood
HEST-1k: A Dataset for Spatial Transcriptomics and Histology Image Analysis. CoRR (2024)
Andrew H. Song, Richard J. Chen, Guillaume Jaume, Anurag J. Vaidya, Alexander S. Baras, Faisal Mahmood
Multimodal Prototyping for cancer survival prediction. CoRR (2024)
Gan Gao, Andrew H. Song, Fiona Wang, David Brenes, Rui Wang, Sarah S. L. Chow, Kevin W. Bishop, Lawrence D. True, Faisal Mahmood, Jonathan T. C. Liu
Triage of 3D pathology data via 2.5D multiple-instance learning to guide pathologist assessments. CoRR (2024)
Andrew H. Song, Guillaume Jaume, Drew F. K. Williamson, Ming Y. Lu, Anurag Vaidya, Tiffany R. Miller, Faisal Mahmood
Artificial Intelligence for Digital and Computational Pathology. CoRR (2024)
Guillaume Jaume, Lukas Oldenburg, Anurag Vaidya, Richard J. Chen, Drew F. K. Williamson, Thomas Peeters, Andrew H. Song, Faisal Mahmood
Transcriptomics-guided Slide Representation Learning in Computational Pathology. CoRR (2024)
ChangGyun Jin, Andrew H. Song, Seong-Eun Kim
Two-Phase Multitask Autoencoder-Based Deep Learning Framework for Subject-Independent EEG Motor Imagery Classification. IEEE Access 12 (2024)
Andrew H. Song, Mane Williams, Drew F. K. Williamson, Guillaume Jaume, Andrew Zhang, Bowen Chen, Robert Serafin, Jonathan T. C. Liu, Alexander S. Baras, Anil V. Parwani, Faisal Mahmood
Weakly Supervised AI for Efficient Analysis of 3D Pathology Samples. CoRR (2023)
Richard J. Chen, Tong Ding, Ming Y. Lu, Drew F. K. Williamson, Guillaume Jaume, Bowen Chen, Andrew Zhang, Daniel Shao, Andrew H. Song, Muhammad Shaban, Mane Williams, Anurag Vaidya, Sharifa Sahai, Lukas Oldenburg, Luca L. Weishaupt, Judy J. Wang, Walt Williams, Long Phi Le, Georg Gerber, Faisal Mahmood
A General-Purpose Self-Supervised Model for Computational Pathology. CoRR (2023)
Alexander Lin, Andrew H. Song, Demba E. Ba
Mixture Model Auto-Encoders: Deep Clustering Through Dictionary Learning. ICASSP (2022)
Iain Carmichael, Andrew H. Song, Richard J. Chen, Drew F. K. Williamson, Tiffany Y. Chen, Faisal Mahmood
Incorporating Intratumoral Heterogeneity into Weakly-Supervised Deep Learning Models via Variance Pooling. MICCAI (2) (2022)
Iain Carmichael, Andrew H. Song, Richard J. Chen, Drew F. K. Williamson, Tiffany Y. Chen, Faisal Mahmood
Incorporating intratumoral heterogeneity into weakly-supervised deep learning models via variance pooling. CoRR (2022)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
Covariance-Free Sparse Bayesian Learning. IEEE Trans. Signal Process. 70 (2022)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
High-Dimensional Sparse Bayesian Learning without Covariance Matrices. CoRR (2022)
Andrew H. Song, Bahareh Tolooshams, Demba E. Ba
Gaussian Process Convolutional Dictionary Learning. IEEE Signal Process. Lett. 29 (2022)
Andrew H. Song, Seong-Eun Kim, Emery N. Brown
Adaptive State-Space Multitaper Spectral Estimation. IEEE Signal Process. Lett. 29 (2022)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
High-Dimensional Sparse Bayesian Learning without Covariance Matrices. ICASSP (2022)
Alexander Lin, Andrew H. Song, Demba E. Ba
Mixture Model Auto-Encoders: Deep Clustering through Dictionary Learning. CoRR (2021)
Alexander Lin, Andrew H. Song, Berkin Bilgic, Demba E. Ba
Covariance-Free Sparse Bayesian Learning. CoRR (2021)
Andrew H. Song, Demba E. Ba, Emery N. Brown
PLSO: A generative framework for decomposing nonstationary time-series into piecewise stationary oscillatory components. UAI (2021)
Andrew H. Song, Bahareh Tolooshams, Demba E. Ba
Gaussian Process Convolutional Dictionary Learning. CoRR (2021)
Bahareh Tolooshams, Ritwik Giri, Andrew H. Song, Umut Isik, Arvindh Krishnaswamy
Channel-Attention Dense U-Net for Multichannel Speech Enhancement. CoRR (2020)
Andrew H. Song, Francisco J. Flores, Demba E. Ba
Convolutional Dictionary Learning With Grid Refinement. IEEE Trans. Signal Process. 68 (2020)
Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba
Convolutional dictionary learning based auto-encoders for natural exponential-family distributions. ICML (2020)
Bahareh Tolooshams, Ritwik Giri, Andrew H. Song, Umut Isik, Arvindh Krishnaswamy
Channel-Attention Dense U-Net for Multichannel Speech Enhancement. ICASSP (2020)
Andrew H. Song, Leon Chlon, Hugo Soulat, John Tauber, Sandya Subramanian, Demba E. Ba, Michael J. Prerau
Multitaper Infinite Hidden Markov Model for EEG. EMBC (2019)
Bahareh Tolooshams, Andrew H. Song, Simona Temereanca, Demba E. Ba
Deep Exponential-Family Auto-Encoders. CoRR (2019)
Andrew H. Song, Francisco J. Flores, Demba E. Ba
Fast Convolutional Dictionary Learning off the Grid. CoRR (2019)
Leon Chlon, Andrew H. Song, Sandya Subramanian, Hugo Soulat, John Tauber, Demba E. Ba, Michael J. Prerau
Multitaper Spectral Estimation HDP-HMMs for EEG Sleep Inference. CoRR (2018)
Andrew H. Song, Sourish Chakravarty, Emery N. Brown
A Smoother State Space Multitaper Spectrogram. EMBC (2018)