Pinned Repositories
awesome-compneuro
A curated list of resources dedicated to Computational Neuroscience
EB1A
EB1A Full Application - I-140 and I-485
nips2016
A list of resources for all invited talks, tutorials, workshops and presentations at NIPS 2016
numpy-ml
Machine learning, in numpy
pandas-cookbook
Recipes for using Python's pandas library
Practical_RL
A course in reinforcement learning in the wild
rDBwrappers
R wrapper-functions for hive/psql
stat-cookbook
The probability and statistics cookbook
UWBeamerPosterTemplate
BeamerPoster Template using UW colors and logo
satpreetsingh's Repositories
satpreetsingh/AAI-site
NYU PSYCH-GA 3405.001 / DS-GA 3001.014 : Advancing AI through cognitive science
satpreetsingh/aima-python
Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"
satpreetsingh/autodidact
A pedagogical implementation of Autograd
satpreetsingh/bayesian-reward-shaping
Bayesian Reward Shaping Framework for Deep Reinforcement Learning
satpreetsingh/communication-subspace
Code for "Cortical areas interact through a communication subspace", Semedo et al. (Neuron, 2018)
satpreetsingh/DDPAE-video-prediction
Learning to Decompose and Disentangle Representations for Video Prediction, NIPS 2018
satpreetsingh/Disentangled-Sequential-Autoencoder
Variational Autoencoder for Unsupervised and Disentangled Representation Learning of content and motion features in sequential data (Mandt et al.).
satpreetsingh/fmriprep
fMRIprep is a functional magnetic resonance image pre-processing pipeline that is designed to provide an easily accessible, state-of-the-art interface that is robust to differences in scan acquisition protocols and that requires minimal user input, while providing easily interpretable and comprehensive error and output reporting.
satpreetsingh/generative-models
Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.
satpreetsingh/grid-cells
Implementation of the supervised learning experiments in Vector-based navigation using grid-like representations in artificial agents, as published at https://www.nature.com/articles/s41586-018-0102-6
satpreetsingh/info-theory
Course Notes for Information Theory
satpreetsingh/InformationBottleneckAlgorithms
Information Bottleneck Algorithms for Relevant-Information-Preserving Signal Processing in Python
satpreetsingh/ISLR-python
An Introduction to Statistical Learning (James, Witten, Hastie, Tibshirani, 2013): Python code
satpreetsingh/learnopencv
Learn OpenCV : C++ and Python Examples
satpreetsingh/loss-landscape
Code for visualizing the loss landscape of neural nets
satpreetsingh/MAT6115_Dynamical_Systems
Support material for MAT6115, Université de Montréal, Fall 2018
satpreetsingh/Multicore-opt-SNE
Parallel opt-SNE implementation with Python wrapper
satpreetsingh/multitask
satpreetsingh/ndap-fa2018
neuro data analysis in python
satpreetsingh/neural-symbolic-machines
Neural Symbolic Machines is a framework to integrate neural networks and symbolic representations using reinforcement learning, with applications in program synthesis and semantic parsing.
satpreetsingh/normalizing-flows
Understanding normalizing flows
satpreetsingh/papaja
papaja (Preparing APA Journal Articles) is an R package that provides document formats and helper functions to produce complete APA manscripts from RMarkdown-files (PDF and Word documents).
satpreetsingh/psl-examples
Various examples to showcase the functionality of PSL.
satpreetsingh/pTSAFall2018
DS-GA 3001.001/.002 Probabilistic time series analysis Fall 2018
satpreetsingh/pycm
Multi-class confusion matrix library in Python.
satpreetsingh/rave
R Analysis and Visualization of ECOG Data
satpreetsingh/recurrent-memory
When do neural networks learn sequential vs. persistent solutions in short-term memory tasks?
satpreetsingh/SpaceRecon
Nonlinear Dynamical Systems (nlds) tools for time-series analysis.
satpreetsingh/StatisticsNotes
Everything I learnt in graduate school in statistics.
satpreetsingh/tigramite
Tigramite is a time series analysis python module for causal discovery. **** Interested in doing a Postdoc/PhD applying machine learning to societally relevant scientific problems at the new DLR Data Science Institute in Germany? Visit www.climateinformaticslab.com **** The Tigramite documentation is at