Austin J. Brockmeier

发表

Learning and exploiting recurrent patterns in neural data

Austin J. Brockmeier, A. Brockmeier, 2014 .

Tensor completion throughmultiple Kronecker product decomposition

Andrzej Cichocki, Austin J. Brockmeier, Anh Huy Phan, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Optimizing microstimulation using a reinforcement learning framework

Austin J. Brockmeier, José Carlos Príncipe, Joseph T. Francis, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control

Austin J. Brockmeier, José Carlos Príncipe, Justin C. Sanchez, 2014, Comput. Intell. Neurosci..

Learning Recurrent Waveforms Within EEGs

Austin J. Brockmeier, José Carlos Príncipe, J. Príncipe, 2016, IEEE Transactions on Biomedical Engineering.

Information-theoretic metric learning: 2-D linear projections of neural data for visualization

Austin J. Brockmeier, José Carlos Príncipe, Luis Gonzalo Sánchez Giraldo, 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

Circular object arrangement using spherical embeddings

Austin J. Brockmeier, Xenophon Evangelopoulos, Tingting Mu, 2020, Pattern Recognit..

Quantifying risk factors in medical reports with a context-aware linear model

Sophia Ananiadou, Austin J. Brockmeier, Piotr Przybyla, 2019, J. Am. Medical Informatics Assoc..

Distributed Document and Phrase Co-embeddings for Descriptive Clustering

Tingting Mu, Sophia Ananiadou, Jun'ichi Tsujii, 2017, EACL.

Joint optimization of algorithmic suites for EEG analysis

Austin J. Brockmeier, Eder Santana, José Carlos Príncipe, 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Self-Tuned Descriptive Document Clustering Using a Predictive Network

Tingting Mu, Sophia Ananiadou, Austin J. Brockmeier, 2018, IEEE Transactions on Knowledge and Data Engineering.

A semi-supervised approach using label propagation to support citation screening

Tingting Mu, Sophia Ananiadou, Austin J. Brockmeier, 2017, J. Biomed. Informatics.

A Graduated Non-Convexity Relaxation for Large Scale Seriation

Tingting Mu, Austin J. Brockmeier, Xenophon Evangelopoulos, 2017, SDM.

A metric approach toward point process divergence

Austin J. Brockmeier, José Carlos Príncipe, Sohan Seth, 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Advances in Neural Information Processing Systems 23 (NIPS 2010)

Austin J. Brockmeier, Sohan Seth, Jose C. Principe, 2010 .

Spatio-temporal clustering of firing rates for neural state estimation

Austin J. Brockmeier, Jose C. Principe, Justin C. Sanchez, 2010, 2010 Annual International Conference of the IEEE Engineering in Medicine and Biology.

Improving reference prioritisation with PICO recognition

Sophia Ananiadou, Austin J. Brockmeier, Meizhi Ju, 2019, BMC Medical Informatics and Decision Making.

Quantifying the Informativeness of Similarity Measurements

Tingting Mu, Sophia Ananiadou, Austin J. Brockmeier, 2017, J. Mach. Learn. Res..

An information-theoretic approach to motor action decoding with a reconfigurable parallel architecture

Alan D. George, Herman Lam, Austin J. Brockmeier, 2011, 2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Continuation methods for approximate large scale object sequencing

Tingting Mu, Austin J. Brockmeier, Xenophon Evangelopoulos, 2018, Machine Learning.

A greedy algorithm for model selection of tensor decompositions

Andrzej Cichocki, Austin J. Brockmeier, José Carlos Príncipe, 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.

Learning multiscale neural metrics via entropy minimization

Austin J. Brockmeier, Jose C. Principe, Joseph T. Francis, 2013, 2013 6th International IEEE/EMBS Conference on Neural Engineering (NER).

An Association Framework to Analyze Dependence Structure in Time Series

Austin J. Brockmeier, Andreas Keil, José Carlos Príncipe, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Projentropy: Using entropy to optimize spatial projections

Austin J. Brockmeier, Eder Santana, José Carlos Príncipe, 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Locating spatial patterns of waveforms during sensory perception in scalp EEG

Austin J. Brockmeier, José Carlos Príncipe, Walter J. Freeman, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Neural Decoding with Kernel-Based Metric Learning

Austin J. Brockmeier, José Carlos Príncipe, Joseph T. Francis, 2014, Neural Computation.

Reinforcement Learning in Video Games Using Nearest Neighbor Interpolation and Metric Learning

Panos M. Pardalos, Austin J. Brockmeier, José Carlos Príncipe, 2016, IEEE Transactions on Computational Intelligence and AI in Games.

A novel family of non-parametric cumulative based divergences for point processes

Austin J. Brockmeier, José Carlos Príncipe, Sohan Seth, 2010, NIPS.

Explicit versus implicit source estimation for blind multiple input single output system identification

Austin J. Brockmeier, José Carlos Príncipe, J. Príncipe, 2015, 2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

Efficient temporal decomposition of local field potentials

Austin J. Brockmeier, José Carlos Príncipe, Justin C. Sanchez, 2011, 2011 IEEE International Workshop on Machine Learning for Signal Processing.

Decoding Algorithms for Brain–Machine Interfaces

Austin J. Brockmeier, Jose C. Principe, J. Príncipe, 2013 .

Evaluating dependence in spike train metric spaces

Austin J. Brockmeier, José Carlos Príncipe, Sohan Seth, 2011, The 2011 International Joint Conference on Neural Networks.

Subspace matching thalamic microstimulation to tactile evoked potentials in rat somatosensory cortex

Austin J. Brockmeier, José Carlos Príncipe, Joseph T. Francis, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Local and Sparse Linear Causal Models for fMRI Resting-State Signals

Austin J. Brockmeier, Hassan Baker, A. Brockmeier, 2021, 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER).

Shift-invariant waveform learning on epileptic ECoG

Austin J. Brockmeier, Carlos H. Mendoza-Cardenas, A. Brockmeier, 2021, 2021 43rd Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC).

Searching for waveforms on spatially-filtered epileptic ECoG

Austin J. Brockmeier, Carlos H. Mendoza-Cardenas, A. Brockmeier, 2021, 2021 10th International IEEE/EMBS Conference on Neural Engineering (NER).

Exploring latent networks in resting-state fMRI using voxel-to-voxel causal modeling feature selection

Austin J. Brockmeier, Hassan Baker, 2021 .