Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, o — from…
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, o — from…
Use ARIS to run Markdown-based agent skills for literature review, idea discovery, cross-model critique, experiment planning, and paper-writing support.
Neuroplastic self-modifying runtime for AI agents. Creates a file-based 'brain' that learns from interactions: reflexes (fast-path responses), habits (learned patterns), weighted…
Use when you have a pre-trained DNN model for retention time prediction and need to adapt it to a new chromatographic method or instrument where you have only 10–20 calibration…
Use when training a DNN on retention time prediction or similar continuous regression tasks where: (1) the feature space is very high-dimensional (thousands of molecular…
Use when when your input includes molecular structures (SMILES, conformers) and you need to predict a continuous property (e.g., CCS, binding affinity, solubility) that depends on…
Use when you have a trained GNN model (stored as .h5 weights) and molecular graph representations (SMILES strings and/or 3D coordinates), and you need to compute predicted CCS…
Synthesize multi-source research (codebase, git history, Slack, web, MCPs) into readable HTML reports — concept explainers, weekly status reports, incident reports, technical…
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, o — from…
Use when the user wants to understand an ML/AI topic, compare approaches, or survey framework capabilities — "how does X work?", "compare X vs Y
ML research for RAN with reinforcement learning, causal inference, and cognitive consciousness integration.
Use when you have MGF or native MS/MS arrays (mz_array, intensity_array, precursor_mz, adduct) and want to predict the most likely molecular formula.
Use when when you have paired or unpaired MS/MS spectra and need to compute structural similarity scores without explicit molecular fingerprint computation, or when you want to…
Use when when training a deep neural network on paired MS/MS spectra to predict structural similarity scores, especially when the training dataset is moderate-sized (109,734…
Use when your input is a corpus of MS/MS spectra with annotated molecular formulas and adduct types that represent a new ionisation mode, instrument type, or adduct chemistry not…
Generates complete conventional non-oncology diagnostic machine-learning research designs from a user-provided disease context, optional mechanism theme, and validation d — from…
Research translation skill for turning QML papers into concrete implementation and evaluation plans.
Use when when you have paired MS/MS spectra with known structural similarity labels (Tanimoto scores from molecular fingerprints) and need to predict structural similarity for new…
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API.
Production-ready reinforcement learning algorithms (PPO, SAC, DQN, TD3, DDPG, A2C) with scikit-learn-like API.
PyTorch Geometric (PyG) for graph neural networks: node/graph classification, link prediction with GCN, GAT, GraphSAGE, GIN.
Use when when you have molecular input data (SMILES strings or graph representations) and need to predict molecular properties or spectra using graph neural networks.
Generates complete non-tumor biomedical machine learning research designs from a user-provided research direction.
Generates complete tumor immune-infiltration-guided bulk-transcriptome diagnostic biomarker and machine-learning research designs from a user-provided cancer type and stu — from…
Adversarial review protocol applied across three domains: external research that informs decisions (research domain — ADR-008), production implementations whose behaviour matters…
Reinforcement learning fundamentals, algorithms, and research