A novel family of non-parametric cumulative based divergences for point processes. - Sohan Seth; Il Memming Park; Austin J. Brockmeier; Mulugeta Semework; John S. Choi; Joseph T. Francis; José Carlos Príncipe (NIPS, 2010)

Optimizing microstimulation using a reinforcement learning framework. - Austin J. Brockmeier; John S. Choi; Marcello M. DiStasio; Joseph T. Francis; José C. Príncipe (EMBC, 2011)

An information-theoretic approach to motor action decoding with a reconfigurable parallel architecture. - Stefan Craciun; Austin J. Brockmeier; Alan D. George; Herman Lam; José C. Príncipe (EMBC, 2011)

A metric approach toward point process divergence. - Sohan Seth; Austin J. Brockmeier; José Carlos Príncipe (ICASSP, 2011)

Evaluating dependence in spike train metric spaces. - Sohan Seth; Austin J. Brockmeier; John S. Choi; Mulugeta Semework; Joseph T. Francis; José C. Príncipe (IJCNN, 2011)

Efficient temporal decomposition of local field potentials. - Austin J. Brockmeier; José C. Príncipe; Babak Mahmoudi; Justin C. Sanchez (MLSP, 2011)

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)

Locating spatial patterns of waveforms during sensory perception in scalp EEG. - Austin J. Brockmeier; Mehrnaz Kh. Hazrati; Walter J. Freeman; Lin Li 020; José C. Príncipe (EMBC, 2012)

An Association Framework to Analyze Dependence Structure in Time Series. - Bilal H. Fadlallah; Austin J. Brockmeier; Sohan Seth; Lin Li 020; Andreas Keil; 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)

A greedy algorithm for model selection of tensor decompositions. - Austin J. Brockmeier; José C. Príncipe; Anh Huy Phan 001; Andrzej Cichocki (ICASSP, 2013)

Tensor completion throughmultiple Kronecker product decomposition. - Anh Huy Phan 001; Andrzej Cichocki; Petr Tichavský; Gheorghe Luta; Austin J. Brockmeier (ICASSP, 2013)

Joint optimization of algorithmic suites for EEG analysis. - Eder Santana; Austin J. Brockmeier; José C. Príncipe (EMBC, 2014)

Projentropy: Using entropy to optimize spatial projections. - Austin J. Brockmeier; Eder Santana; Luis Gonzalo Sánchez Giraldo; José C. Príncipe (ICASSP, 2014)

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control. - Lin Li 020; Austin J. Brockmeier; John S. Choi; Joseph T. Francis; Justin C. Sanchez; José C. Príncipe (Comput. Intell. Neurosci., 2014)

Neural Decoding with Kernel-Based Metric Learning. - Austin J. Brockmeier; John S. Choi; Evan G. Kriminger; Joseph T. Francis; José C. Príncipe (Neural Comput., 2014)

Explicit versus implicit source estimation for blind multiple input single output system identification. - Austin J. Brockmeier; José C. Príncipe (ICASSP, 2015)

Learning Recurrent Waveforms Within EEGs. - Austin J. Brockmeier; José C. Príncipe (IEEE Trans. Biomed. Eng., 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)

Distributed Document and Phrase Co-embeddings for Descriptive Clustering. - Motoki Sato; Austin J. Brockmeier; Georgios Kontonatsios; Tingting Mu; John Yannis Goulermas; Jun'ichi Tsujii; Sophia Ananiadou (EACL (1), 2017)

A Graduated Non-Convexity Relaxation for Large Scale Seriation. - Xenophon Evangelopoulos; Austin J. Brockmeier; Tingting Mu; John Yannis Goulermas (SDM, 2017)

A semi-supervised approach using label propagation to support citation screening. - Georgios Kontonatsios; Austin J. Brockmeier; Piotr Przybyla; John McNaught; Tingting Mu; John Yannis Goulermas; Sophia Ananiadou (J. Biomed. Informatics, 2017)

Quantifying the Informativeness of Similarity Measurements. - Austin J. Brockmeier; Tingting Mu; Sophia Ananiadou; John Yannis Goulermas (J. Mach. Learn. Res., 2017)

Self-Tuned Descriptive Document Clustering Using a Predictive Network. - Austin J. Brockmeier; Tingting Mu; Sophia Ananiadou; John Yannis Goulermas (IEEE Trans. Knowl. Data Eng., 2018)

Quantifying risk factors in medical reports with a context-aware linear model. - Piotr Przybyla; Austin J. Brockmeier; Sophia Ananiadou (J. Am. Medical Informatics Assoc., 2019)

Improving reference prioritisation with PICO recognition. - Austin J. Brockmeier; Meizhi Ju; Piotr Przybyla; Sophia Ananiadou (BMC Medical Informatics Decis. Mak., 2019)

Continuation methods for approximate large scale object sequencing. - Xenophon Evangelopoulos; Austin J. Brockmeier; Tingting Mu; John Yannis Goulermas (Mach. Learn., 2019)

Circular object arrangement using spherical embeddings. - Xenophon Evangelopoulos; Austin J. Brockmeier; Tingting Mu; John Yannis Goulermas (Pattern Recognit., 2020)

Shift-invariant waveform learning on epileptic ECoG. - Carlos H. Mendoza-Cardenas; Austin J. Brockmeier (EMBC, 2021)

Local and Sparse Linear Causal Models for fMRI Resting-State Signals. - Hassan Baker; Austin J. Brockmeier (NER, 2021)

Searching for waveforms on spatially-filtered epileptic ECoG. - Carlos H. Mendoza-Cardenas; Austin J. Brockmeier (NER, 2021)

The Representation Jensen-Rényi Divergence. - Jhoan Keider Hoyos-Osorio; Oscar Skean; Austin J. Brockmeier; Luis Gonzalo Sánchez Giraldo (ICASSP, 2022)

DiME: Maximizing Mutual Information by a Difference of Matrix-Based Entropies. - Oscar Skean; Jhoan Keider Hoyos-Osorio; Austin J. Brockmeier; Luis Gonzalo Sánchez Giraldo (CoRR, 2023)

Partial Optimal Transport for Support Subset Selection. - Bilal Riaz; Yuksel Karahan; Austin J. Brockmeier (Trans. Mach. Learn. Res., 2023)

Exploring the influence of functional architecture on cortical thickness networks in early psychosis - A longitudinal study. - Kristina M. Holton; Shi Yu Chan; Austin J. Brockmeier; Dost Öngür; Mei-Hua Hall (NeuroImage, 2023)

Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex. - Alex Mulrooney; Austin J. Brockmeier (CoRR, 2024)

Anomaly Detection via Autoencoder Composite Features and NCE. - Yalin Liao; Austin J. Brockmeier (CoRR, 2025)

Patch2Loc: Learning to Localize Patches for Unsupervised Brain Lesion Detection. - Hassan Baker; Austin J. Brockmeier (CoRR, 2025)

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

Latent Growth Models of Longitudinal Changes in Functional Connectivity during Early Stage Psychosis. - Kristina M. Holton; Shi Yu Chan; Austin J. Brockmeier; Mei-Hua Hall (Neuroinformatics, 2025)