behdad13
Applied ML/AI researcher focused on Time-series Forecasting, NLP, and combining ML with OR.
HEC Montréal Montreal
behdad13's Stars
SkalskiP/courses
This repository is a curated collection of links to various courses and resources about Artificial Intelligence (AI)
bentrevett/pytorch-seq2seq
Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText.
iryna-kondr/scikit-llm
Seamlessly integrate LLMs into scikit-learn.
Nixtla/neuralforecast
Scalable and user friendly neural :brain: forecasting algorithms.
AIStream-Peelout/flow-forecast
Deep learning PyTorch library for time series forecasting, classification, and anomaly detection (originally for flood forecasting).
cure-lab/LTSF-Linear
[AAAI-23 Oral] Official implementation of the paper "Are Transformers Effective for Time Series Forecasting?"
datamllab/tods
TODS: An Automated Time-series Outlier Detection System
oliverguhr/transformer-time-series-prediction
proof of concept for a transformer-based time series prediction model
guillaume-chevalier/seq2seq-signal-prediction
Signal forecasting with a Sequence-to-Sequence (seq2seq) Recurrent Neural Network (RNN) model in TensorFlow - Guillaume Chevalier
curiousily/Deep-Learning-For-Hackers
Machine Learning tutorials with TensorFlow 2 and Keras in Python (Jupyter notebooks included) - (LSTMs, Hyperameter tuning, Data preprocessing, Bias-variance tradeoff, Anomaly Detection, Autoencoders, Time Series Forecasting, Object Detection, Sentiment Analysis, Intent Recognition with BERT)
maxjcohen/transformer
Implementation of Transformer model (originally from Attention is All You Need) applied to Time Series.
lixus7/Time-Series-Works-Conferences
Time-Series Work Summary in CS Top Conferences (NIPS, ICML, ICLR, KDD, AAAI, WWW, IJCAI, CIKM, ICDM, ICDE, etc.)
QData/spacetimeformer
Multivariate Time Series Forecasting with efficient Transformers. Code for the paper "Long-Range Transformers for Dynamic Spatiotemporal Forecasting."
MAZiqing/FEDformer
JEddy92/TimeSeries_Seq2Seq
This repo aims to be a useful collection of notebooks/code for understanding and implementing seq2seq neural networks for time series forecasting. Networks are constructed with keras/tensorflow.
lkulowski/LSTM_encoder_decoder
Build a LSTM encoder-decoder using PyTorch to make sequence-to-sequence prediction for time series data
nok-halfspace/Transformer-Time-Series-Forecasting
vrcarva/vmdpy
Variational mode decomposition (VMD) in Python
jinglescode/time-series-forecasting-pytorch
Acquiring data from Alpha Vantage and predicting stock prices with PyTorch's LSTM
FateMurphy/CEEMDAN_LSTM
CEEMDAN_LSTM is a Python project for decomposition-integration forecasting models based on EMD methods and LSTM.
stevinc/Transformer_Timeseries
Pytorch code for Google's Temporal Fusion Transformer
PyPSA/pypsa-usa
PyPSA-USA: An Open-Source Energy System Optimization Model for the United States
ctxj/Time-Series-Transformer-Pytorch
dyq0811/EEG-Transformer-seq2seq
Modified transformer network utilizing the attention mechanism for time series or any other numerical data. 6.100 project at MIT Media Lab.
OrigamiSL/TCCT2021
Convolutional Transformer Architectures Complementary to Time Series Forecasting Transformer Models
samluxenberg1/Time-Series-Forecasting-with-Wavelets
KurochkinAlexey/ConvRNN
Pytorch implementation of Autoregressive Convolutional Recurrent Neural Network for Univariate and Multivariate Time Series Prediction https://arxiv.org/pdf/1907.04155.pdf
Doheon/TimeSeriesForecast-Informer
behdad13/TriConvGRU
A Novel Time-series Forecasting Model Applied in Ontario Electricity Market (Master's Thesis)
behdad13/Time_Series_Forecasting_DL
Many DL Models, Optimized by the Bayesian Method, Implemented to Forecast the Electricity Demand in Toronto, CA.