Subspace matching thalamic microstimulation to tactile evoked potentials in rat somatosensory cortex. - Austin J. Brockmeier; John S. Choi; Matthew S. Emigh; Lin Li 020; Joseph T. Francis; José C. Príncipe (EMBC, 2012)

Information-theoretic metric learning: 2-D linear projections of neural data for visualization. - Austin J. Brockmeier; Luis Gonzalo Sánchez Giraldo; Matthew S. Emigh; Jihye Bae; John S. Choi; Joseph T. Francis; José C. Príncipe (EMBC, 2013)

Linear discriminant analysis with an information divergence criterion. - Matthew Emigh; Evan Kriminger; José C. Príncipe (IJCNN, 2015)

A model based approach to exploration of continuous-state MDPs using Divergence-to-Go. - Matthew Emigh; Evan Kriminger; José Carlos Príncipe (MLSP, 2015)

Information Theoretic-Learning auto-encoder. - Eder Santana; Matthew Emigh; José C. Príncipe (IJCNN, 2016)

Exploiting Spatio-Temporal Structure with Recurrent Winner-Take-All Networks. - Eder Santana; Matthew Emigh; Pablo Zerges; José C. Príncipe (CoRR, 2016)

Reinforcement Learning in Video Games Using Nearest Neighbor Interpolation and Metric Learning. - Matthew Emigh; Evan G. Kriminger; Austin J. Brockmeier; José C. Príncipe; Panos M. Pardalos (IEEE Trans. Comput. Intell. AI Games, 2016)

Autoencoders trained with relevant information: Blending Shannon and Wiener's perspectives. - Shujian Yu; Matthew Emigh; Eder Santana; José C. Príncipe (ICASSP, 2017)

Exploiting Spatio-Temporal Structure With Recurrent Winner-Take-All Networks. - Eder Santana; Matthew S. Emigh; Pablo Zegers; José C. Príncipe (IEEE Trans. Neural Networks Learn. Syst., 2018)

Guided Policy Exploration for Markov Decision Processes Using an Uncertainty-Based Value-of-Information Criterion. - Isaac J. Sledge; Matthew S. Emigh; José C. Príncipe (IEEE Trans. Neural Networks Learn. Syst., 2018)

Algorithmic Design and Implementation of Unobtrusive Multistatic Serial LiDAR Image. - Chi Ding; Zheng Cao; Matthew S. Emigh; José C. Príncipe; Bing Ouyang; Anni K. Vuorenkoski; Fraser R. Dalgleish; Brian Ramos; Yanjun Li 003 (CoRR, 2019)

Target Detection and Segmentation in Circular-Scan Synthetic-Aperture-Sonar Images using Semi-Supervised Convolutional Encoder-Decoders. - Isaac J. Sledge; Matthew S. Emigh; Jonathan L. King; Denton L. Woods; J. Tory Cobb; José C. Príncipe (CoRR, 2021)

Advances in Self-Supervised Learning for Synthetic Aperture Sonar Data Processing, Classification, and Pattern Recognition. - Brandon Sheffield; Frank E. Bobe III; Bradley Marchand; Matthew S. Emigh (CoRR, 2023)

Weakly Supervised Object Segmentation by Background Conditional Divergence. - Hassan Baker; Matthew S. Emigh; Austin J. Brockmeier (CoRR, 2025)