├── .gitignore ├── README.md ├── assets └── figures │ ├── book-cover │ └── gatam-book-cover.png │ ├── chapter05 │ ├── chronos-paper-figure-1.png │ ├── paper-lagllama-figure-1.png │ ├── paper-lagllama-figure-2.png │ ├── wavenet-paper-figure2.png │ └── wavernet-paper-figure3.png │ ├── chapter06 │ ├── timevae-paper-figure-1.png │ └── timevae-paper-figure-2.png │ └── chapter08 │ └── timegan-paper-figure-1a.png ├── chapter01 ├── BIL.csv ├── BIL_annualized_returns_20_day_MA.csv ├── BIL_last_100_days.csv ├── BIL_returns.csv ├── BIL_returns_last_100_days.csv ├── Indices.csv ├── Indices.xlsx ├── Indices_daily_returns.csv ├── SPY_last_100_days.csv ├── SPY_returns_last_100_days.csv └── inputDataOHLCDaily_ETF_20150417.csv ├── chapter02 ├── CRSP_mid.csv ├── CRSP_nextMonthReturns.csv ├── F-F_Research_Data_Factors_daily.CSV └── ombined_FF_30dReturn.csv ├── chapter04 └── EvaluationGenerativeModels.ipynb ├── chapter05 ├── ChronosZeroShot.ipynb ├── GlounTSTutorial.ipynb ├── LSTMModel.ipynb ├── LagLlamaZeroShot.ipynb ├── LinearARModel.ipynb ├── NaiveModel.ipynb └── ProbabilisticNeuralARModel.ipynb ├── chapter06 ├── MNIST_VAE_2D.ipynb └── TimeVAE.ipynb ├── chapter07 ├── NiceFlows.ipynb └── RealNVPFlow.ipynb ├── chapter08 ├── MNIST_GAN_2D.ipynb ├── RGAN.ipynb └── TimeGAN.ipynb ├── chapter10 ├── DatasetsTutorial.ipynb ├── FinbertDistillationCompression.ipynb ├── LLAMA_3_1_Finetune_Finance.ipynb └── PipelinesTutorial.ipynb ├── genai4t ├── __init__.py ├── chapters │ ├── __init__.py │ ├── flows │ │ ├── core.py │ │ ├── nice.py │ │ └── realnvp.py │ ├── gans │ │ ├── __init__.py │ │ ├── core.py │ │ ├── quantgan.py │ │ └── timegan.py │ └── vae │ │ ├── __init__.py │ │ ├── core.py │ │ └── timevae.py ├── data │ └── processing.py ├── evaluation │ ├── __init__.py │ ├── generation │ │ ├── __init__.py │ │ ├── bp.py │ │ ├── core.py │ │ ├── discriminator.py │ │ ├── predictive.py │ │ ├── util.py │ │ └── visualize.py │ ├── metrics.py │ └── simple_evaluator.py ├── forecasting │ ├── __init__.py │ ├── data.py │ ├── predictors │ │ ├── ar.py │ │ ├── chronos.py │ │ ├── lag_llama │ │ │ ├── __init__.py │ │ │ ├── data │ │ │ │ ├── __init__.py │ │ │ │ ├── augmentations │ │ │ │ │ ├── __init__.py │ │ │ │ │ ├── augmentations.py │ │ │ │ │ ├── freq_mask.py │ │ │ │ │ └── freq_mix.py │ │ │ │ ├── data_utils.py │ │ │ │ ├── dataset_list.py │ │ │ │ └── read_new_dataset.py │ │ │ ├── gluon │ │ │ │ ├── __init__.py │ │ │ │ ├── estimator.py │ │ │ │ └── lightning_module.py │ │ │ ├── gluon_utils │ │ │ │ ├── __init__.py │ │ │ │ ├── gluon_ts_distributions │ │ │ │ │ ├── __init__.py │ │ │ │ │ └── implicit_quantile_network.py │ │ │ │ └── scalers │ │ │ │ │ ├── __init__.py │ │ │ │ │ └── robust_scaler.py │ │ │ └── model │ │ │ │ ├── __init__.py │ │ │ │ └── module.py │ │ ├── lin_ar.py │ │ ├── lstm.py │ │ ├── naive.py │ │ ├── prob_ar.py │ │ └── util.py │ └── util.py ├── model │ ├── __init__.py │ ├── core.py │ ├── layers.py │ └── utils.py ├── plot_style │ └── plot_style.py └── utils.py └── pyproject.toml 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