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Running on Zero
ADjayantan
EpiADR-Net: Added baseline toggle, bootstrap CIs, Tanimoto applicability domain, fixed formula drift, and ruff CI linting
ee07e36 | # EpiADR-Net Architectural Blueprint & Tensor Operations | |
| This document outlines the detailed tensor dimensions, layer specifications, and mathematical operations across the EpiADR-Net neural pipeline. | |
| --- | |
| ## 📐 Tensor Operations Map | |
| ``` | |
| Input SMILES String | |
| │ | |
| ▼ | |
| Atom Feature Extraction ─────────► Node Matrix X : [N, 5] | |
| Edge Connectivity ─────────► Edge Index E : [2, M] | |
| GTEx Tissue Profile ─────────► Tissue Vector V: [B, 128] | |
| │ | |
| ▼ | |
| Linear Input Projection ─────────► h_0 : [N, 128] | |
| │ | |
| ▼ | |
| 4-Layer GAT Backbone ─────────► h_4 : [N, 128] | |
| Attention α_4 : [M] | |
| │ | |
| ▼ | |
| FiLM Modulation Layer ─────────► γ, β : [B, 128] -> [N, 128] | |
| h_conditioned : [N, 128] | |
| │ | |
| ▼ | |
| Dual Graph Pooling ─────────► [Mean || Max] : [B, 256] | |
| │ | |
| ▼ | |
| 10-Class Classification ─────────► Logits : [B, 10] | |
| Probabilities μ : [B, 10] | |
| Uncertainty σ : [B, 10] | |
| ``` | |
| --- | |
| ## 🔬 Layer Specifications | |
| | Layer Name | Input Shape | Output Shape | Parameters / Operations | | |
| | :--- | :--- | :--- | :--- | | |
| | **Input Linear** | `[N, 5]` | `[N, 128]` | $W_{\text{in}} \in \mathbb{R}^{5 \times 128}$, Bias | | |
| | **GAT Layer 1-4** | `[N, 128]` | `[N, 128]` | $W_{\text{gat}} \in \mathbb{R}^{128 \times 128}, a \in \mathbb{R}^{256 \times 1}$, LeakyReLU | | |
| | **Gene Pathway Cross-Attn**| `[N, 1536]` | `[N, 1536]` | $\text{MultiHeadCrossAttn}(\mathbf{Q}_{1536}, \mathbf{K}_{1024}, \mathbf{V}_{1024})$ | | |
| | **FiLM Residual Update** | `[N, 1536]` | `[N, 1536]` | $h_i^{\text{cond}} = h_i \odot (1.0 + \gamma_{\text{nodes}}) + \beta_{\text{nodes}}$ | | |
| | **Dual Graph Pool**| `[N, 128]` | `[B, 256]` | MeanPool `[B, 128]` \|\| MaxPool `[B, 128]` | | |
| | **Classifier FC1** | `[B, 256]` | `[B, 128]` | Linear(256->128), ReLU, Dropout(0.2) | | |
| | **Classifier FC2** | `[B, 128]` | `[B, 10]` | Linear(128->10) | | |