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06/01/2023
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains
Latent Gaussian process (GP) models are widely used in neuroscience to u...
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05/31/2023
FEED PETs: Further Experimentation and Expansion on the Disambiguation of Potentially Euphemistic Terms
Transformers have been shown to work well for the task of English euphem...
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05/18/2023
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics
Latent variable models have become instrumental in computational neurosc...
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01/13/2023
OA-BEV: Bringing Object Awareness to Bird's-Eye-View Representation for Multi-Camera 3D Object Detection
The recent trend for multi-camera 3D object detection is through the uni...
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03/10/2022
Program Repair: Automated vs. Manual
Various automated program repair (APR) techniques have been proposed to ...
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09/24/2021
MORSE-STF: A Privacy Preserving Computation System
Privacy-preserving machine learning has become a popular area of researc...
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04/08/2021
One-bit Spectrum Sensing with the Eigenvalue Moment Ratio Approach
One-bit analog-to-digital converter (ADC), performing signal sampling as...
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10/26/2020
P^2 Net: Augmented Parallel-Pyramid Net for Attention Guided Pose Estimation
We propose an augmented Parallel-Pyramid Net (P^2 Net) with feature refi...
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10/23/2020
Rescuing neural spike train models from bad MLE
The standard approach to fitting an autoregressive spike train model is ...
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09/02/2020
Non-parametric generalized linear model
A fundamental problem in statistical neuroscience is to model how neuron...
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07/21/2020
Machine Learning in Population and Public Health
Research in population and public health focuses on the mechanisms betwe...
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03/17/2020
Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation
The target of human pose estimation is to determine body part or joint l...
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02/23/2020
On the Role of Dataset Quality and Heterogeneity in Model Confidence
Safety-critical applications require machine learning models that output...
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06/04/2019
Streaming Variational Monte Carlo
Nonlinear state-space models are powerful tools to describe dynamical st...
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02/24/2019
Bi-Skip: A Motion Deblurring Network Using Self-paced Learning
A fast and effective motion deblurring method has great application valu...
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09/27/2018
Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk
ICU mortality risk prediction is a tough yet important task. On one hand...
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06/12/2018
Are My EHRs Private Enough? -Event-level Privacy Protection
Privacy is a major concern in sharing human subject data to researchers ...
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07/27/2017
Recursive Variational Bayesian Dual Estimation for Nonlinear Dynamics and Non-Gaussian Observations
State space models provide an interpretable framework for complex time s...
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04/11/2016
