levi-ackman Goto Github PK

ai_exp_3

ai_exp_tasks_2

autoformer

About Code release for "Autoformer: Decomposition Transformers with Auto-Correlation for Long-Term Series Forecasting" (NeurIPS 2021), https://arxiv.org/abs/2106.13008

benchmarking-gnns

Repository for benchmarking graph neural networks

crossformer

Official implementation of our ICLR 2023 paper "Crossformer: Transformer Utilizing Cross-Dimension Dependency for Multivariate Time Series Forecasting"

d2l-en

Interactive deep learning book with multi-framework code, math, and discussions. Adopted at 500 universities from 70 countries including Stanford, MIT, Harvard, and Cambridge.

eag-rs

EAG-RS: A Novel Explainability-guided ROI Selection Framework for ASD diagnosis via Inter-regional Relation Learning - PyTorch Implementation (IEEE-TMI 2023)

evalplus

EvalPlus for rigourous evaluation of LLM-synthesized code

fast-robust-stl

Unofficial implementation of "Fast RobustSTL: Efficient and Robust Seasonal-Trend Decomposition for Time Series with Complex Patterns"

fedformer

fits

FITS: Frequency Interpolation Time Series Analysis Baseline

graph-neural-network-note

A blog for understanding graph neural network

how-to-download-abide-preprocessed-dataset-for-autism-detection

This script automates the download of preprocessed brain imaging data from the ABIDE dataset, focusing on a specific derivative, preprocessing pipeline, and noise-removal strategy. It filters participants by diagnosis (autism or controls) and downloads relevant data, streamlining research on autism spectrum disorder.

itransformer

Official implementation for "iTransformer: Inverted Transformers Are Effective for Time Series Forecasting" (ICLR 2024 Spotlight), https://openreview.net/forum?id=JePfAI8fah

leddam

[ICML 2024] Official implementation of: "Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling".

lift

The official implementation of LIFT (ICLR'24). Rethinking Channel Dependence for Multivariate Time Series Forecasting: Learning from Leading Indicators.

ltsf-linear

This is the official implementation for AAAI-23 Oral paper "Are Transformers Effective for Time Series Forecasting?"

machine-learning-collection

A resource for learning about Machine learning & Deep Learning

mildlyoverfitted

Paper implementations from scratch and machine learning tutorials

moderntcn

This is an official implementation of "ModernTCN: A Modern Pure Convolution Structure for General Time Series Analysis" (ICLR 2024 Spotlight), https://openreview.net/forum?id=vpJMJerXHU

msd-mixer

A Multi-Scale Decomposition MLP-Mixer for Time Series Analysis

mts-mixers

MTS-Mixers: Multivariate Time Series Forecasting via Factorized Temporal and Channel Mixing

multivariate-time-series-data

my_dp

My_deep_learning_code_example

paradise

patchtst

An offical implementation of PatchTST: "A Time Series is Worth 64 Words: Long-term Forecasting with Transformers." (ICLR 2023) https://arxiv.org/abs/2211.14730

query-selector

LONG-TERM SERIES FORECASTING WITH QUERYSELECTOR – EFFICIENT MODEL OF SPARSEATTENTION

rebutall_icml2024

An Anonymized link for reviewer to further explore paper: Revitalizing Multivariate Time Series Forecasting: Learnable Decomposition with Inter-Series Dependencies and Intra-Series Variations Modeling

robuststl

Unofficial Implementation of RobustSTL: A Robust Seasonal-Trend Decomposition Algorithm for Long Time Series (AAAI 2019)

sam_web