r-shruthi11
Neuroscience grad student at Princeton Neuroscience Institute and @murthylab
Princeton. NJ
Pinned Repositories
arhmm-celegans
B-SOID
Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.
bams
PyTorch implementation of BAMS (https://multiscale-behavior.github.io/)
cs228-notes
Course notes for CS228: Probabilistic Graphical Models.
Deep-Learning-Experiments
Notes and experiments to understand deep learning concepts
dynamax
State Space Models library in JAX
EvidenceApprox
Evidence approximation methods in SSMs
fly-vr
FlyVR is code for design and control of multisensory virtual reality experiments for flies.
flybody
MuJoCo fruit fly body model and reinforcement learning tasks
glm_utils
r-shruthi11's Repositories
r-shruthi11/arhmm-celegans
r-shruthi11/B-SOID
Behavioral segmentation of open field in DeepLabCut, or B-SOID ("B-side"), is a pipeline that pairs unsupervised pattern recognition with supervised classification to achieve fast predictions of behaviors that are not predefined by users.
r-shruthi11/bams
PyTorch implementation of BAMS (https://multiscale-behavior.github.io/)
r-shruthi11/cs228-notes
Course notes for CS228: Probabilistic Graphical Models.
r-shruthi11/Deep-Learning-Experiments
Notes and experiments to understand deep learning concepts
r-shruthi11/dynamax
State Space Models library in JAX
r-shruthi11/EvidenceApprox
Evidence approximation methods in SSMs
r-shruthi11/fly-vr
FlyVR is code for design and control of multisensory virtual reality experiments for flies.
r-shruthi11/flybody
MuJoCo fruit fly body model and reinforcement learning tasks
r-shruthi11/glm_utils
r-shruthi11/glmhmm
code to fit GLMs, HMMs, and GLM-HMMs (aka IO-HMMs)
r-shruthi11/jax-moseq
r-shruthi11/jPCA
jPCA for Neural Data Analysis in Python
r-shruthi11/Kalman-and-Bayesian-Filters-in-Python
Kalman Filter book using Jupyter Notebook. Focuses on building intuition and experience, not formal proofs. Includes Kalman filters,extended Kalman filters, unscented Kalman filters, particle filters, and more. All exercises include solutions.
r-shruthi11/keypoint-moseq
r-shruthi11/keypointMoSeq
r-shruthi11/motionmapperpy
Modified Python 3.0 implementation of MotionMapper (https://github.com/gordonberman/MotionMapper)
r-shruthi11/natneuro-latex-template
LaTeX manuscript template based on a Nature Neuroscience submission
r-shruthi11/pml2-book
Probabilistic Machine Learning: Advanced Topics
r-shruthi11/pyGLMHMM
A Python implementation of GLM-HMM (port of https://github.com/murthylab/GLMHMM)
r-shruthi11/pytorch-Deep-Learning
Deep Learning (with PyTorch)
r-shruthi11/pytorch-the-hard-way
r-shruthi11/r-shruthi11.github.io
r-shruthi11/sleap-io
Standalone utilities for SLEAP pose tracking data.
r-shruthi11/SOM-VAE
TensorFlow implementation of the SOM-VAE model as described in https://arxiv.org/abs/1806.02199
r-shruthi11/ssm
Bayesian learning and inference for state space models
r-shruthi11/stats271sp2021
Material for STATS271: Applied Bayesian Statistics (Spring 2021)
r-shruthi11/test_screen_calibration
r-shruthi11/VAME
Variational Animal Motion Embedding