Pinned Repositories
-chanlun
缠论量化，人类历史上第一个数学上可以严格证明的技术分析策略，包含严格笔，线段作为最低级别，中枢的构成，级别的扩展，第一二三类买卖点，同级别分解的，背驰的判断，区间套，需要技术合作的加微信17866148858，备注"github"。走势分解例子在readme,因海外通达信无法方便接收实时行情，用大智慧制作的走势分解程序，减轻脑力工作量。因时间有限只和有缠论技术基础的人交流。可解决比如走势递归的划分，如何同级别分解，二买三买的低点到底当下如何判断在何处，小转大的程序判断等问题。用缠论主观交易就能稳定赚钱。只有用缠论主观交易能挣钱的人，才有可能量化交易也挣钱。何次交易，本人都可以明确在当下，不知道后续走势的情况下指出其错误所在，从而在当时避免错误。如果交易能亏损很多，用亏损的钱的十分之一学习到能避免重复的亏损的问题，大大的值得了。 缠论的难点在于，同级别分解如何分解，同级别分解的多义性，背驰力度的计算，小转大卖点的处理，跳空等极端走势对走势划分的影响，卖点比买点级别小的把握，中枢震荡的操作，如何规避T+1,等等。
3dbraingen
Official Pytorch Implementation of "Generation of 3D Brain MRI Using Auto-Encoding Generative Adversarial Network" (accepted by MICCAI 2019)
3DCNN-Vis
Visual Explanations From Deep 3D Convolutional Neural Networks for Alzheimer's Disease Classification
3dtopoplot
ACEnet-for-Neuroanatomy-Segmentation
ACEnet: Anatomical Context-Encoding Network for Neuroanatomy Segmentation
ad_examples
A collection of anomaly detection methods (iid/point-based, graph and time series) including active learning for anomaly detection/discovery, bayesian rule-mining, description for diversity/explanation/interpretability. Analysis of incorporating label feedback with ensemble and tree-based detectors. Includes adversarial attacks with Graph Convolutional Network.
alphacsc
Convolution dictionary learning for time-series
ann4brains
Artificial neural networks for brain networks
LEICA
This respository contains the most up-to-date version of the LEICA (Leading Eigenvector Independent Component Analysis)
smriprep
Structural MRI PREProcessing (sMRIPrep) workflows for NIPreps (NeuroImaging PREProcessing tools)
Zeigar's Repositories
Zeigar/LEICA
This respository contains the most up-to-date version of the LEICA (Leading Eigenvector Independent Component Analysis)
Zeigar/brainsmash
Brain Surrogate Maps with Autocorrelated Spatial Heterogeneity
Zeigar/C-PAC-1
Configurable Pipeline for the Analysis of Connectomes
Zeigar/control_package
A toolbox for implementing Network Control Theory analyses in python
Zeigar/dashboard
tigrlab dashboard development
Zeigar/dcm2niix
dcm2nii DICOM to NIfTI converter: compiled versions available from NITRC
Zeigar/EEG_denoising_method
Holo-Hilbert spectral-based noise removal method for EEG high-frequency bands
Zeigar/ENIGMA
The ENIGMA Toolbox is an open-source repository for accessing 100+ ENIGMA statistical maps, visualizing cortical and subcortical surface data, and relating neuroimaging findings to micro- and macroscale brain organization. 🤠
Zeigar/eprime3-lsl-package-file
E-Prime 3.0 package to enable LSL.
Zeigar/event_detection
Individualized event structure drives individual differences in whole-brain functional connectivity, NeuroImage Volume 252, 15 May 2022, 118993
Zeigar/GED_tutorial
Code accompanying publication on GED tutorial, Cohen, M. X. A tutorial on generalized eigendecomposition for denoising, contrast enhancement, and dimension reduction in multichannel electrophysiology. NeuroImage 247, 118809, doi:https://doi.org/10.1016/j.neuroimage.2021.118809 (2022).
Zeigar/ggseg
Plotting tool for brain atlases, in ggplot
Zeigar/KSmodel_fMRIdynamics
Modular origins of high-amplitude cofluctuations in fine-scale functional connectivity dynamics, PNAS, November 8, 2021 | 118 (46) e2109380118
Zeigar/LAYNII
Stand alone fMRI software suite for layer-fMRI analyses.
Zeigar/Mansson_etal_2022_BiolPsychiatry
Månsson, K. N., Waschke, L., Manzouri, A., Furmark, T., Fischer, H., & Garrett, D. D. (2022). Moment-to-moment brain signal variability reliably predicts psychiatric treatment outcome. Biological Psychiatry, 91(7), 658-666.
Zeigar/MDMR_fMRI
Zeigar/med2image
Converts medical images to more displayable formats, e.g. NIfTI to jpg.
Zeigar/MedMNIST
[v1 (ISBI'21) + v2] MedMNIST: A Large-Scale Lightweight Benchmark for 2D and 3D Biomedical Image Classification
Zeigar/MITK
The Medical Imaging Interaction Toolkit.
Zeigar/muxViz
Analysis and Visualization of Interconnected Multilayer Networks
Zeigar/network_TDA_tutorial
A hands-on tutorial on network and topological neuroscience
Zeigar/nipy
Neuroimaging in Python FMRI analysis package
Zeigar/nonstandard_modularity_maximization
Modularity maximization as a flexible and generic framework for brain network exploratory analysis,NeuroImage Volume 244, 1 December 2021, 118607
Zeigar/papto
Brady, B., & Bardouille, T. (2022). Periodic/Aperiodic parameterization of transient oscillations (PAPTO)–Implications for healthy ageing. NeuroImage, 251, 118974.
Zeigar/PyDDM
A drift-diffusion modeling (DDM) framework for Python3
Zeigar/pydeface
A tool to remove facial structure from MRI images.
Zeigar/sr_enn
Constructing neural network models from brain data reveals representational transformations linked to adaptive behavior. Nat Commun 2022, 673.
Zeigar/suarez_neuromorphicnetworks
Code supporting Suarez et al., Learning function from structure in neuromorphic networks. Nat Mach Intell 3, 771–786 (2021).
Zeigar/TAAC
TMS Adaptable Auditory Control
Zeigar/tedana
TE-dependent analysis of multi-echo fMRI