Search Results - "Livezey, Jesse A"

Deep learning as a tool for neural data analysis: Speech classification and cross-frequency coupling in human sensorimotor cortex by Livezey, Jesse A, Bouchard, Kristofer E, Chang, Edward F

“…A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from…”
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Deep learning approaches for neural decoding across architectures and recording modalities by Livezey, Jesse A, Glaser, Joshua I

“…Abstract Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool…”
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Improved inference in coupling, encoding, and decoding models and its consequence for neuroscientific interpretation by Sachdeva, Pratik S., Livezey, Jesse A., Dougherty, Maximilian E., Gu, Bon-Mi, Berke, Joshua D., Bouchard, Kristofer E.

“…•An improved statistical inference algorithm enhances sparsity at no prediction cost.•Highly sparse coupling models exhibit elevated community…”
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Attending to experimental physics practices and lifelong learning skills in an introductory laboratory course by Gandhi, Punit R., Livezey, Jesse A., Zaniewski, Anna M., Reinholz, Daniel L., Dounas-Frazer, Dimitri R.

“…We have designed an introductory laboratory course that engaged first-year undergraduate students in two complementary types of iteration: (1) iterative…”
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A Tale of Two Slinkies: Learning about Model Building in a Student-Driven Classroom by Berggren, Calvin, Gandhi, Punit, Livezey, Jesse A, Olf, Ryan

“…We describe a set of conceptual and hands-on activities based around understanding the dynamics of a Slinky that is hung vertically and released from rest…”
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The geometry of correlated variability leads to highly suboptimal discriminative sensory coding by Livezey, Jesse A, Sachdeva, Pratik S, Dougherty, Maximilian E, Summers, Mathew T, Bouchard, Kristofer E

“…The brain represents the world through the activity of neural populations; however, whether the computational goal of sensory coding is to support…”
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Deep learning approaches for neural decoding across architectures and recording modalities by Livezey, Jesse A., Glaser, Joshua I.

“…Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool for…”
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Learning and Inferring Representations of Data in Neural Networks by Livezey, Jesse A

“…Finding useful representations of data in order to facilitate scientific knowledge generation is a ubiquitous concept across disciplines. Until the development…”
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Deep learning approaches for neural decoding: from CNNs to LSTMs and spikes to fMRI by Livezey, Jesse A, Glaser, Joshua I

“…Decoding behavior, perception, or cognitive state directly from neural signals has applications in brain-computer interface research as well as implications…”
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Unsupervised Discovery of Temporal Structure in Noisy Data with Dynamical Components Analysis by Clark, David G, Livezey, Jesse A, Bouchard, Kristofer E

“…NeurIPS 14267-14278 (2019) Linear dimensionality reduction methods are commonly used to extract low-dimensional structure from high-dimensional data. However,…”
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Hangul Fonts Dataset: a Hierarchical and Compositional Dataset for Investigating Learned Representations by Livezey, Jesse A, Hwang, Ahyeon, Yeung, Jacob, Bouchard, Kristofer E

“…Hierarchy and compositionality are common latent properties in many natural and scientific datasets. Determining when a deep network's hidden activations…”
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Deep learning as a tool for neural data analysis: speech classification and cross-frequency coupling in human sensorimotor cortex by Livezey, Jesse A, Bouchard, Kristofer E, Chang, Edward F

“…A fundamental challenge in neuroscience is to understand what structure in the world is represented in spatially distributed patterns of neural activity from…”
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Spiking Linear Dynamical Systems on Neuromorphic Hardware for Low-Power Brain-Machine Interfaces by Clark, David G, Livezey, Jesse A, Chang, Edward F, Bouchard, Kristofer E

“…Neuromorphic architectures achieve low-power operation by using many simple spiking neurons in lieu of traditional hardware. Here, we develop methods for…”
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Learning overcomplete, low coherence dictionaries with linear inference by Livezey, Jesse A, Bujan, Alejandro F, Sommer, Friedrich T

“…JMLR 20(174) 1-42 (2019) Finding overcomplete latent representations of data has applications in data analysis, signal processing, machine learning,…”
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Attending to experimental physics practices and lifelong learning skills in an introductory laboratory course by Gandhi, Punit R, Livezey, Jesse A, Zaniewski, Anna M, Reinholz, Daniel L, Dounas-Frazer, Dimitri R

“…Am. J. Phys. 84, 696 (2016) We have designed an introductory laboratory course that engaged first-year undergraduate students in two complementary types of…”
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Discovering Hidden Factors of Variation in Deep Networks by Cheung, Brian, Livezey, Jesse A, Bansal, Arjun K, Olshausen, Bruno A

“…Deep learning has enjoyed a great deal of success because of its ability to learn useful features for tasks such as classification. But there has been less…”
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