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Found 22 papers, 4 papers with code
Large-scale variational Gaussian state-space models
We introduce an amortized variational inference algorithm and structured variational approximation for state-space models with nonlinear dynamics driven by Gaussian noise.
MEDs for PETs: Multilingual Euphemism Disambiguation for Potentially Euphemistic Terms
This study investigates the computational processing of euphemisms, a universal linguistic phenomenon, across multiple languages.
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains
In this work, we propose cvHM, a general inference framework for latent GP models leveraging Hida-Mat\'ern kernels and conjugate computation variational inference (CVI).
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 euphemism disambiguation, in which a potentially euphemistic term (PET) is classified as euphemistic or non-euphemistic in a particular context.
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics
Latent variable models have become instrumental in computational neuroscience for reasoning about neural computation.
Low-frequency Image Deep Steganography: Manipulate the Frequency Distribution to Hide Secrets with Tenacious Robustness
By avoiding high-frequency artifacts and manipulating the frequency distribution of the embedded feature map, LIDS achieves improved robustness against attacks that distort the high-frequency components of container images.
OA-BEV: Bringing Object Awareness to Bird's-Eye-View Representation for Multi-Camera 3D Object Detection
To this end, we propose OA-BEV, a network that can be plugged into the BEV-based 3D object detection framework to bring out the objects by incorporating object-aware pseudo-3D features and depth features.
COSINE: A Web Server for Clonal and Subclonal Structure Inference and Evolution in Cancer Genomics
In the past decade, a variety of methods have been developed for subclonal reconstruction using bulk tumor sequencing data.
Multidimensional Information Assisted Deep Learning Realizing Flexible Recognition of Vortex Beam Modes
Recognition of OAM modes unlimited by distance and sign of TC achieved by MIADLFR method can make optical communication and detection by OAM light much more attractive.
Optics Image and Video Processing Medical Physics
$P^2$ Net: Augmented Parallel-Pyramid Net for Attention Guided Pose Estimation
We propose a refinement stage for the pyramid features to further boost the accuracy of our network.
Rescuing neural spike train models from bad MLE
The standard approach to fitting an autoregressive spike train model is to maximize the likelihood for one-step prediction.
Non-parametric generalized linear model
However, obtaining a satisfactory fit often requires burdensome model selection and fine tuning the form of the basis functions and their temporal span.
Machine Learning in Population and Public Health
Research in population and public health focuses on the mechanisms between different cultural, social, and environmental factors and their effect on the health, of not just individuals, but communities as a whole.
Augmented Parallel-Pyramid Net for Attention Guided Pose-Estimation
At last, we proposed a differentiable auto data augmentation method to further improve estimation accuracy.
On the Role of Dataset Quality and Heterogeneity in Model Confidence
We demonstrate that this leads to heterogenous confidence/accuracy behavior in the test data and is poorly handled by the standard calibration algorithms.
Streaming Variational Monte Carlo
Nonlinear state-space models are powerful tools to describe dynamical structures in complex time series.
Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection
To address this problem, we propose a multiple receptive field and small-object-focusing weakly-supervised segmentation network (MRFSWSnet) to achieve fast object detection.
Bi-Skip: A Motion Deblurring Network Using Self-paced Learning
A fast and effective motion deblurring method has great application values in real life.
Learning Better Features for Face Detection with Feature Fusion and Segmentation Supervision
We assume that problems inside are inadequate use of supervision information and imbalance between semantics and details at all level feature maps in CNN even with Feature Pyramid Networks (FPN).
Supervised Nonnegative Matrix Factorization to Predict ICU Mortality Risk
We used the simulation data to verify the effectiveness of this method, and then we applied it to ICU mortality risk prediction and demonstrated its superiority over other conventional supervised NMF methods.
Variational online learning of neural dynamics
It brings the challenge of learning both latent neural state and the underlying dynamical system because neither is known for neural systems a priori.
Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains
In the V1 dataset, we find that vLGP achieves substantially higher performance than previous methods for predicting omitted spike trains, as well as capturing both the toroidal topology of visual stimuli space, and the noise-correlation.
