Skill Claude CodeCodex
Selects the top-N most informative tiles from a gigapixel whole slide image by ranking on pixel intensity sum, keeping tiles with the most tissue content.
Skill Claude CodeCodex
Selects the top-N most informative tiles from a gigapixel whole slide image by ranking on pixel intensity sum, keeping tiles with the most tissue content.
Skill Claude CodeCodex
Pre-shard TFRecords into N files each balanced along 3 axes (patient, target, image-count), then KFold over file indices for leak-free triple-stratified folds.
Skill Claude CodeCodex
Extract volumetric features from 3D segmentation masks including scan/tumor pixel ratios, tumor percentage, and tumor centroid coordinates.
Skill Claude CodeCodex
Tversky loss with independent alpha/beta constants to separately penalize false positives and false negatives in imbalanced segmentation.
Skill Claude CodeCodex
Train segmentation with BCE loss first for stable convergence, then fine-tune with Lovasz-hinge on raw logits for IoU-optimal predictions.
Skill Claude CodeCodex
Chain a study-level classifier with an image-level detector, merging class probabilities and bounding boxes into a unified prediction.
Skill Claude CodeCodex
Use a lightweight slice-classifier to find the Z-range containing an organ in a CT volume, then crop and trilinear-resample that sub-volume into a fixed shape for a heavier 3D classifier — replaces "use the whole volume" with "use only the relevant slab" at a fraction of the FLOPs.
Skill Claude CodeCodex
Efficiently sample N evenly-spaced frames from a video using OpenCV grab/retrieve pattern with optional resize for batch face detection or classification.
Skill Claude CodeCodex
Extracts calibrated yes/no probabilities from a VQA model by masking all logits except yes/no token variants and renormalizing via softmax.
Skill Claude CodeCodex
Combines gradual learning rate warmup with cosine annealing decay for stable fine-tuning of pretrained models.
Skill Claude CodeCodex
Propagates image-level multi-labels to individual instances as weak supervision for instance-level training.
Skill Claude CodeCodex
BCE loss with per-class asymmetric positive/negative weights to match competition metrics or handle class imbalance in multilabel classification.
Skill Claude CodeCodex
Ensemble predictions from heterogeneous vision-language models by blending their output embeddings with fixed scalar weights in embedding space.
Skill Claude CodeCodex
Convert bounding boxes between YOLO (normalized center), VOC (absolute corners), and COCO (absolute xywh) formats with image dimension scaling.
Skill Claude CodeCodex
Load large LLMs with 4-bit NF4 quantization and optional double quantization via BitsAndBytes to reduce GPU memory by 4x while preserving inference quality.
Skill Claude CodeCodex
Shared-backbone neural network with actor (policy) and critic (value) heads for grid-based game agent RL training.
Skill Claude CodeCodex
Dynamically reduce maxtokens and batch size as wall-clock time approaches a cutoff to ensure all inputs get processed.
Skill Claude CodeCodex
Ensemble multi-model LLM predictions using weighted combination of average probability, cross-model agreement ratio, and max confidence.
Skill Claude CodeCodex
Parse sequential yes/no answers to build inclusion/exclusion sets, then apply compound boolean filters to narrow a candidate list.
Skill Claude CodeCodex
Steers LLM output format by injecting a partial assistant response into the chat template before generation, forcing structured output without fine-tuning.
Skill Claude CodeCodex
Batch-compute perplexity for multiple texts using a causal LM with proper padding, shifted labels, and pad-token masking for efficient GPU utilization.
Skill Claude CodeCodex
Force-clamp free-form LLM output to binary yes/no with keyword matching and a fallback default for constrained environments.
Skill Claude CodeCodex
Hierarchical binary search over entity space by asking category, region, then first-letter questions to narrow candidates before guessing.
Skill Claude CodeCodex
Extract final numeric answers from LaTeX \boxed{} notation in LLM math reasoning output, scanning matches in reverse for robustness.
At most 3 mods per repository are shown here, and a mod shipped inside a plugin is left to that plugin's page — the rest are on their repository pages: