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Austin J. Brockmeier
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2020 – today
- 2024
- [i5]Alex Mulrooney, Austin J. Brockmeier:
Contrastive Learning to Fine-Tune Feature Extraction Models for the Visual Cortex. CoRR abs/2410.06067 (2024) - 2023
- [j13]Kristina M. Holton
, Shi Yu Chan
Exploring the influence of functional architecture on cortical thickness networks in early psychosis - A longitudinal study. NeuroImage 274: 120127 (2023) - [j12]Bilal Riaz, Yuksel Karahan, Austin J. Brockmeier:
Partial Optimal Transport for Support Subset Selection. Trans. Mach. Learn. Res. 2023 (2023) - [i4]Oscar Skean, Jhoan Keider Hoyos-Osorio, Austin J. Brockmeier, Luis Gonzalo Sánchez Giraldo:
DiME: Maximizing Mutual Information by a Difference of Matrix-Based Entropies. CoRR abs/2301.08164 (2023) - 2022
- [c21]Jhoan Keider Hoyos-Osorio, Oscar Skean
The Representation Jensen-Rényi Divergence. ICASSP 2022: 4313-4317 - 2021
- [c20]Carlos H. Mendoza-Cardenas, Austin J. Brockmeier
Shift-invariant waveform learning on epileptic ECoG. EMBC 2021: 1136-1139 - [c19]Hassan Baker, Austin J. Brockmeier
Local and Sparse Linear Causal Models for fMRI Resting-State Signals. NER 2021: 162-165 - [c18]Carlos H. Mendoza-Cardenas, Austin J. Brockmeier
Searching for waveforms on spatially-filtered epileptic ECoG. NER 2021: 403-406 - [i3]Carlos H. Mendoza-Cardenas, Austin J. Brockmeier:
Searching for waveforms on spatially-filtered epileptic ECoG. CoRR abs/2103.13853 (2021) - [i2]Carlos H. Mendoza-Cardenas, Austin J. Brockmeier:
Shift-invariant waveform learning on epileptic ECoG. CoRR abs/2108.03177 (2021) - [i1]Jhoan Keider Hoyos-Osorio, Oscar Skean, Austin J. Brockmeier, Luis Gonzalo Sánchez Giraldo:
The Representation Jensen-Rényi Divergence. CoRR abs/2112.01583 (2021) - 2020
- [j11]Xenophon Evangelopoulos, Austin J. Brockmeier
Circular object arrangement using spherical embeddings. Pattern Recognit. 103: 107192 (2020)
2010 – 2019
- 2019
- [j10]Piotr Przybyla
Quantifying risk factors in medical reports with a context-aware linear model. J. Am. Medical Informatics Assoc. 26(6): 537-546 (2019) - [j9]Austin J. Brockmeier
Improving reference prioritisation with PICO recognition. BMC Medical Informatics Decis. Mak. 19(1): 256 (2019) - [j8]Xenophon Evangelopoulos, Austin J. Brockmeier
Continuation methods for approximate large scale object sequencing. Mach. Learn. 108(4): 595-626 (2019) - 2018
- [j7]Austin J. Brockmeier
Self-Tuned Descriptive Document Clustering Using a Predictive Network. IEEE Trans. Knowl. Data Eng. 30(10): 1929-1942 (2018) - 2017
- [j6]Georgios Kontonatsios
A semi-supervised approach using label propagation to support citation screening. J. Biomed. Informatics 72: 67-76 (2017) - [j5]Austin J. Brockmeier, Tingting Mu, Sophia Ananiadou, John Yannis Goulermas:
Quantifying the Informativeness of Similarity Measurements. J. Mach. Learn. Res. 18: 76:1-76:61 (2017) - [c17]Motoki Sato, Austin J. Brockmeier
Distributed Document and Phrase Co-embeddings for Descriptive Clustering. EACL (1) 2017: 991-1001 - [c16]Xenophon Evangelopoulos, Austin J. Brockmeier
A Graduated Non-Convexity Relaxation for Large Scale Seriation. SDM 2017: 462-470 - 2016
- [j4]Austin J. Brockmeier
Learning Recurrent Waveforms Within EEGs. IEEE Trans. Biomed. Eng. 63(1): 43-54 (2016) - [j3]Matthew Emigh, Evan G. Kriminger, Austin J. Brockmeier
Reinforcement Learning in Video Games Using Nearest Neighbor Interpolation and Metric Learning. IEEE Trans. Comput. Intell. AI Games 8(1): 56-66 (2016) - 2015
- [c15]Austin J. Brockmeier
Explicit versus implicit source estimation for blind multiple input single output system identification. ICASSP 2015: 2140-2144 - 2014
- [j2]Lin Li
A Tensor-Product-Kernel Framework for Multiscale Neural Activity Decoding and Control. Comput. Intell. Neurosci. 2014: 870160:1-870160:16 (2014) - [j1]Austin J. Brockmeier
Neural Decoding with Kernel-Based Metric Learning. Neural Comput. 26(6): 1080-1107 (2014) - [c14]Eder Santana, Austin J. Brockmeier
Joint optimization of algorithmic suites for EEG analysis. EMBC 2014: 2997-3000 - [c13]Austin J. Brockmeier
Projentropy: Using entropy to optimize spatial projections. ICASSP 2014: 4538-4542 - 2013
- [c12]Austin J. Brockmeier
Information-theoretic metric learning: 2-D linear projections of neural data for visualization. EMBC 2013: 5586-5589 - [c11]Anh Huy Phan
Tensor completion throughmultiple Kronecker product decomposition. ICASSP 2013: 3233-3237 - [c10]Austin J. Brockmeier
A greedy algorithm for model selection of tensor decompositions. ICASSP 2013: 6113-6117 - 2012
- [c9]Austin J. Brockmeier
Locating spatial patterns of waveforms during sensory perception in scalp EEG. EMBC 2012: 2531-2534 - [c8]Austin J. Brockmeier
Subspace matching thalamic microstimulation to tactile evoked potentials in rat somatosensory cortex. EMBC 2012: 2957-2960 - [c7]Bilal H. Fadlallah, Austin J. Brockmeier
An Association Framework to Analyze Dependence Structure in Time Series. EMBC 2012: 6176-6179 - 2011
- [c6]Austin J. Brockmeier
Optimizing microstimulation using a reinforcement learning framework. EMBC 2011: 1069-1072 - [c5]Stefan Craciun, Austin J. Brockmeier
An information-theoretic approach to motor action decoding with a reconfigurable parallel architecture. EMBC 2011: 4621-4624 - [c4]Sohan Seth, Austin J. Brockmeier
A metric approach toward point process divergence. ICASSP 2011: 2104-2107 - [c3]Sohan Seth, Austin J. Brockmeier
Evaluating dependence in spike train metric spaces. IJCNN 2011: 2645-2652 - [c2]Austin J. Brockmeier
Efficient temporal decomposition of local field potentials. MLSP 2011: 1-6 - 2010
- [c1]Sohan Seth, Il Memming Park, Austin J. Brockmeier, Mulugeta Semework, John S. Choi, Joseph T. Francis, José Carlos Príncipe:
A novel family of non-parametric cumulative based divergences for point processes. NIPS 2010: 2119-2127
Coauthor Index
aka: José Carlos Príncipe
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last updated on 2024-11-19 20:42 CET by the dblp team
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