AI & LLM Engineering · K-Dense-AI/scientific-agent-skills

Plans and audits runs of the HypoGeniC and HypoRefine packages, which propose hypotheses from labeled text datasets, with local checks before any model call.

K-Dense-AI/scientific-agent-skills

Analyzes user-requested Screenpipe history windows to detect repeated research workflows, match existing scientific skills, and stage new skill drafts or composition recipes for review.

K-Dense-AI/scientific-agent-skills

Organizes research with the self-hosted Open Notebook alternative to NotebookLM.

K-Dense-AI/scientific-agent-skills

Applies Arbor Hypothesis Tree Refinement to research artifacts with repeatable evaluators, including model training, agent harnesses, data synthesis and benchmark optimization.

K-Dense-AI/scientific-agent-skills

Uses the Biohub esm Python SDK for ESM3 protein generation, ESMC embeddings, and ESMFold2 all-atom folding.

K-Dense-AI/scientific-agent-skills

Extracts and preprocesses whole-slide histology image tiles with Histolab.

K-Dense-AI/scientific-agent-skills

Modal is a serverless cloud platform for running Python on demand, including on-demand GPUs.

K-Dense-AI/scientific-agent-skills

GPU-accelerates scientific Python on NVIDIA hardware and verifies that the result is correct and faster.

K-Dense-AI/scientific-agent-skills

Builds with and operates Pi, the minimal terminal coding harness.

K-Dense-AI/scientific-agent-skills

Version-aware guidance for PufferLib reinforcement-learning environments, vectorization, policies, PuffeRL training, evaluation, and safe checkpoint review.

K-Dense-AI/scientific-agent-skills

Trains and evaluates single-agent reinforcement learning with Stable Baselines3 (PPO, SAC, DQN, TD3, DDPG, A2C), Gymnasium custom environments, vectorized rollouts, callbacks, and checkpoint…

K-Dense-AI/scientific-agent-skills

Supports work with Outpost Bio's open microbiome foundation models - the Waypoint checkpoints (Waypoint-6m, Waypoint-45m, Waypoint-170m), the Atlas pretraining corpus, the Compass eight-task…

K-Dense-AI/scientific-agent-skills

Deep learning framework (PyTorch Lightning / lightning package).

K-Dense-AI/scientific-agent-skills

Supports PyTorch Geometric (PyG) graph neural networks — node/link/graph classification, message passing (GCN, GAT, GraphSAGE, GIN), heterogeneous graphs, neighbor sampling, and custom datasets.

K-Dense-AI/scientific-agent-skills

Generates transcriptome-wide virtual spatial transcriptomics from H&E histology with DeepSpot-M.

K-Dense-AI/scientific-agent-skills

Featurizes small molecules with Molfeat for QSAR/QSPR, chemical similarity, virtual screening, and molecular ML.

K-Dense-AI/scientific-agent-skills

Hugging Face Transformers for loading Hub models, running pipeline inference, text generation, and Trainer fine-tuning on NLP, vision, audio, and multimodal tasks.

K-Dense-AI/scientific-agent-skills

Applies UMAP-learn to nonlinear dimensionality reduction, 2D/3D embeddings, clustering preprocessing, supervised or semi-supervised UMAP, DensMAP, AlignedUMAP, and Parametric UMAP workflows.

K-Dense-AI/scientific-agent-skills