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ae_general_4d

transcriptomics
dimensionality-reduction
ae
general
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ae_general_4d
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{
  "model_info": {
    "latent_dims": 4,
    "compression_mode": "samples",
    "model_type": "SimpleAE",
    "input_dim": 2405,
    "layer_sizes": [
      2405,
      2048,
      1024,
      512,
      256,
      4
    ],
    "saved_model_file": "autoencoder_4_latent_dims_oos_mode.pt"
  },
  "training_config": {
    "n_epochs": 5000,
    "batch_size": 64,
    "learning_rate": 0.0001,
    "patience": 100,
    "scheduler": "cosine",
    "optimizer": "Adam",
    "loss_function": "adaptive",
    "preprocessing_method": "robust"
  },
  "enhanced_features": {
    "use_simple_ae": true,
    "use_denoising_warmup": true,
    "denoising_epochs": 15,
    "use_curriculum_learning": true,
    "curriculum_warmup_epochs": 50,
    "curriculum_initial_percentile": 0.5,
    "use_adaptive_batchnorm": true,
    "correlation_weight": 0.1
  },
  "data_config": {
    "datasets": [
      "tracerx",
      "cellfm",
      "gtex"
    ],
    "data_path": "../datasets/TRACERx/tracerx_vst_counts_proper.csv",
    "normalization_range": "[-1, 1]",
    "harmonization_method": "imputation",
    "imputation_strategy": "dataset_median",
    "tracerx_priority_weight": 2.0
  },
  "training_results": {
    "best_epoch": 0,
    "best_validation_loss": 0.00014691724548943324,
    "final_epoch": 0,
    "training_completed": true
  },
  "system_info": {
    "device": "cuda:0",
    "timestamp": "2025-08-26T23:08:39.446881",
    "python_version": "3.10.12",
    "pytorch_version": "2.6.0+cu124"
  }
}